From b3c4b71e10306a0cec76eaa9a39691954a971490 Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 12:18:36 +0200 Subject: [PATCH 01/19] independent gpu usage control of kwave and PAM, 2d accruacy figure --- README.md | 21 ++ scripts/run_pam.jl | 24 +- scripts/run_pam_3d_focused_sweep.jl | 3 +- scripts/run_pam_3d_jitter_bandwidth_sweep.jl | 3 +- scripts/run_pam_3d_vessel_sweep.jl | 3 +- scripts/run_pam_overnight_sweep.jl | 6 +- scripts/run_pam_sweep.jl | 6 +- src/pam/sweep.jl | 2 + src/pam/workflow.jl | 15 +- validation/2D_PAM_Accuracy/plot_results.jl | 273 ++++++++++++++++++ validation/2D_PAM_Accuracy/results.md | 16 + .../results_20260509_114048_fig7.pdf | Bin 0 -> 1009745 bytes validation/2D_PAM_Accuracy/run_validation.jl | 240 +++++++++++++++ 13 files changed, 588 insertions(+), 24 deletions(-) create mode 100644 validation/2D_PAM_Accuracy/plot_results.jl create mode 100644 validation/2D_PAM_Accuracy/results.md create mode 100644 validation/2D_PAM_Accuracy/results_20260509_114048_fig7.pdf create mode 100644 validation/2D_PAM_Accuracy/run_validation.jl diff --git a/README.md b/README.md index e24ce4f..047823a 100644 --- a/README.md +++ b/README.md @@ -712,6 +712,27 @@ For skull sweeps, requested targets are filtered so that only points inside the - `result.jld2` - `cases/`: one figure per retained target, each showing uncorrected vs corrected reconstruction +## Validation + +### 2D PAM localization accuracy (Schoen & Arvanitis 2020, Table II / Fig. 7) + +`validation/2D_PAM_Accuracy/run_validation.jl` reproduces the point-source localization sweep from the reference paper. +A rectangular grid of 1 MHz sources (axial 30–80 mm, lateral ±20 mm) is simulated through a human skull with k-Wave and reconstructed with both the homogeneous ASA and the heterogeneous ASA (HASA, Eq. 6). +Errors are reported for three receiver apertures (50, 75, 100 mm), matching Table II of the paper. + +**k-Wave simulation always runs on GPU.** +PAM reconstruction runs on CPU by default; pass `--recon-use-gpu` to use the GPU for reconstruction as well. + +```bash +# k-Wave GPU, reconstruction CPU +julia --project=. validation/2D_PAM_Accuracy/run_validation.jl + +# k-Wave GPU, reconstruction GPU +julia --project=. validation/2D_PAM_Accuracy/run_validation.jl --recon-use-gpu +``` + +Results are saved as `validation/2D_PAM_Accuracy/results_.jld2` and a comparison table is printed to stdout. + ## Tests Run the standard test suite: diff --git a/scripts/run_pam.jl b/scripts/run_pam.jl index 30b4348..e3632f8 100644 --- a/scripts/run_pam.jl +++ b/scripts/run_pam.jl @@ -60,7 +60,8 @@ function parse_cli(args) "lens-lateral-radius-mm" => "12", "aberrator-c" => "1700", "aberrator-rho" => "1150", - "use-gpu" => "false", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", "recon-bandwidth-khz" => "500", "recon-step-um" => "50", "recon-mode" => "auto", @@ -202,7 +203,6 @@ function apply_model_defaults!(opts, provided_keys::Set{String}) !("num-cycles" in provided_keys) && (opts["num-cycles"] = "5") !("phase-mode" in provided_keys) && (opts["phase-mode"] = "coherent") !("recon-step-um" in provided_keys) && (opts["recon-step-um"] = "50") - !("use-gpu" in provided_keys) && (opts["use-gpu"] = "true") end source_model = parse_source_model(opts["source-model"]) if dimension == 3 && source_model in (:squiggle, :network) @@ -910,7 +910,8 @@ function run_pam_case_3d( cfg::PAMConfig3D; frequencies::Union{Nothing, AbstractVector{<:Real}}=nothing, bandwidth::Real=0.0, - use_gpu::Bool=false, + kwave_use_gpu::Bool=true, + recon_use_gpu::Bool=true, reconstruction_axial_step::Union{Nothing, Real}=nothing, reconstruction_mode::Symbol=:full, window_config::PAMWindowConfig=PAMWindowConfig(), @@ -922,7 +923,7 @@ function run_pam_case_3d( rng::Random.AbstractRNG=Random.default_rng(), source_variability::SourceVariabilityConfig=SourceVariabilityConfig(), ) - use_gpu || error("3D PAM reconstruction currently requires --use-gpu=true.") + recon_use_gpu || error("3D PAM reconstruction currently requires --recon-use-gpu=true.") recon_freqs = isnothing(frequencies) ? default_recon_frequencies(sources) : Float64.(frequencies) phase_mode = TranscranialFUS._normalize_source_phase_mode(source_phase_mode) recon_mode = phase_mode == :random_phase_per_window ? @@ -953,7 +954,7 @@ function run_pam_case_3d( error("3D PAM does not implement --source-phase-mode=random_phase_per_realization yet.") end rf, grid, sim_info = if sim_mode == :kwave - simulate_point_sources_3d(c, rho, sim_sources, cfg; use_gpu=use_gpu) + simulate_point_sources_3d(c, rho, sim_sources, cfg; use_gpu=kwave_use_gpu) else analytic_rf_for_point_sources_3d(cfg, sim_sources) end @@ -962,7 +963,7 @@ function run_pam_case_3d( bandwidth=bandwidth, reference_sound_speed=TranscranialFUS._pam_reference_sound_speed(c, cfg, sources), axial_step=reconstruction_axial_step, - use_gpu=use_gpu, + use_gpu=recon_use_gpu, show_progress=show_progress, benchmark=benchmark, window_batch=window_batch, @@ -1010,7 +1011,8 @@ function run_pam_case_3d( :source_phase_mode => phase_mode, :n_frames => n_frames, :window_config => TranscranialFUS._window_config_info(effective_window_config), - :use_gpu => use_gpu, + :kwave_use_gpu => kwave_use_gpu, + :recon_use_gpu => recon_use_gpu, :show_progress => show_progress, ) end @@ -2025,7 +2027,8 @@ if dimension == 3 cfg; frequencies=recon_frequencies, bandwidth=recon_bandwidth_hz, - use_gpu=parse_bool(opts["use-gpu"]), + kwave_use_gpu=parse_bool(opts["kwave-use-gpu"]), + recon_use_gpu=parse_bool(opts["recon-use-gpu"]), reconstruction_axial_step=parse(Float64, opts["recon-step-um"]) * 1e-6, reconstruction_mode=reconstruction_mode, window_config=window_config, @@ -2243,7 +2246,8 @@ if isempty(from_run_dir) cfg; frequencies=recon_frequencies, bandwidth=recon_bandwidth_hz, - use_gpu=parse_bool(opts["use-gpu"]), + use_gpu=parse_bool(opts["recon-use-gpu"]), + kwave_use_gpu=parse_bool(opts["kwave-use-gpu"]), reconstruction_axial_step=parse(Float64, opts["recon-step-um"]) * 1e-6, analysis_mode=analysis_mode, peak_method=peak_method, @@ -2343,7 +2347,7 @@ else simulation_info=simulation_info, frequencies=recon_frequencies, bandwidth=recon_bandwidth_hz, - use_gpu=parse_bool(opts["use-gpu"]), + use_gpu=parse_bool(opts["recon-use-gpu"]), reconstruction_axial_step=parse(Float64, opts["recon-step-um"]) * 1e-6, analysis_mode=analysis_mode, peak_method=peak_method, diff --git a/scripts/run_pam_3d_focused_sweep.jl b/scripts/run_pam_3d_focused_sweep.jl index c8175d6..08a9e99 100644 --- a/scripts/run_pam_3d_focused_sweep.jl +++ b/scripts/run_pam_3d_focused_sweep.jl @@ -56,7 +56,8 @@ function focused_base_args(opts) "frequency-jitter-percent" => "1", "axial-gain-power" => "1.5", "sim-mode" => "kwave", - "use-gpu" => "true", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", "window-batch" => "2", "recon-progress" => "false", "random-seed" => opts["random-seed"], diff --git a/scripts/run_pam_3d_jitter_bandwidth_sweep.jl b/scripts/run_pam_3d_jitter_bandwidth_sweep.jl index dd41718..3b26664 100644 --- a/scripts/run_pam_3d_jitter_bandwidth_sweep.jl +++ b/scripts/run_pam_3d_jitter_bandwidth_sweep.jl @@ -51,7 +51,8 @@ function jitter_bandwidth_base_args(opts) "auto-threshold-max" => opts["auto-threshold-max"], "auto-threshold-step" => opts["auto-threshold-step"], "sim-mode" => "kwave", - "use-gpu" => "true", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", "window-batch" => "2", "recon-progress" => "false", "random-seed" => opts["random-seed"], diff --git a/scripts/run_pam_3d_vessel_sweep.jl b/scripts/run_pam_3d_vessel_sweep.jl index 24ef3f2..7b6c5c4 100644 --- a/scripts/run_pam_3d_vessel_sweep.jl +++ b/scripts/run_pam_3d_vessel_sweep.jl @@ -53,7 +53,8 @@ function vessel_base_args(opts) "auto-threshold-max" => opts["auto-threshold-max"], "auto-threshold-step" => opts["auto-threshold-step"], "sim-mode" => "kwave", - "use-gpu" => "true", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", "window-batch" => "2", "recon-progress" => "false", "random-seed" => opts["random-seed"], diff --git a/scripts/run_pam_overnight_sweep.jl b/scripts/run_pam_overnight_sweep.jl index e27237e..68a12dc 100644 --- a/scripts/run_pam_overnight_sweep.jl +++ b/scripts/run_pam_overnight_sweep.jl @@ -23,7 +23,8 @@ function parse_cli(args) "auto-threshold-min" => "0.10", "auto-threshold-max" => "0.95", "auto-threshold-step" => "0.01", - "use-gpu" => "false", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", "dry-run" => "false", "force" => "false", ) @@ -69,7 +70,8 @@ function common_sim_args(opts; seed=opts["random-seed"]) "slice-index" => opts["slice-index"], "skull-transducer-distance-mm" => opts["skull-transducer-distance-mm"], "random-seed" => seed, - "use-gpu" => opts["use-gpu"], + "kwave-use-gpu" => opts["kwave-use-gpu"], + "recon-use-gpu" => opts["recon-use-gpu"], "boundary-threshold-ratios" => opts["boundary-threshold-ratios"], "auto-threshold-search" => opts["auto-threshold-search"], "auto-threshold-min" => opts["auto-threshold-min"], diff --git a/scripts/run_pam_sweep.jl b/scripts/run_pam_sweep.jl index 8cef29a..6cdfc28 100644 --- a/scripts/run_pam_sweep.jl +++ b/scripts/run_pam_sweep.jl @@ -38,7 +38,8 @@ function parse_cli(args) "lens-lateral-radius-mm" => "12", "aberrator-c" => "1700", "aberrator-rho" => "1150", - "use-gpu" => "false", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", ) for arg in args @@ -447,7 +448,8 @@ sweep_results = run_pam_sweep( cfg; frequencies=[parse(Float64, opts["frequency-mhz"]) * 1e6], example_targets_mm=example_targets_mm, - use_gpu=parse_bool(opts["use-gpu"]), + use_gpu=parse_bool(opts["recon-use-gpu"]), + kwave_use_gpu=parse_bool(opts["kwave-use-gpu"]), case_callback=case_callback, ) diff --git a/src/pam/sweep.jl b/src/pam/sweep.jl index 202ac6c..48a26ec 100644 --- a/src/pam/sweep.jl +++ b/src/pam/sweep.jl @@ -168,6 +168,7 @@ function run_pam_sweep( frequencies::Union{Nothing, AbstractVector{<:Real}}=nothing, example_targets_mm::Union{Nothing, AbstractVector{<:Tuple{<:Real, <:Real}}}=nothing, use_gpu::Bool=false, + kwave_use_gpu::Bool=false, runner::Function=run_pam_case, case_callback::Union{Nothing, Function}=nothing, ) @@ -196,6 +197,7 @@ function run_pam_sweep( cfg; frequencies=frequencies, use_gpu=use_gpu, + kwave_use_gpu=kwave_use_gpu, ) stats_geo = results[:stats_geo] stats_hasa = results[:stats_hasa] diff --git a/src/pam/workflow.jl b/src/pam/workflow.jl index ed28a14..3b3aabd 100644 --- a/src/pam/workflow.jl +++ b/src/pam/workflow.jl @@ -27,7 +27,7 @@ function _run_pam_per_window( sources::AbstractVector{<:EmissionSource2D}, cfg::PAMConfig; source_phase_mode::Symbol, - use_gpu::Bool, + kwave_use_gpu::Bool, rng::Random.AbstractRNG, recon_kwargs::NamedTuple, variability::SourceVariabilityConfig=SourceVariabilityConfig(), @@ -46,7 +46,7 @@ function _run_pam_per_window( accumulation=win_cfg.accumulation, ) eff_recon_kwargs = merge(recon_kwargs, (reconstruction_mode=:windowed, window_config=eff_window_config)) - rf, kgrid, sim_info = simulate_point_sources(c, rho, expanded, cfg; use_gpu=use_gpu) + rf, kgrid, sim_info = simulate_point_sources(c, rho, expanded, cfg; use_gpu=kwave_use_gpu) results = reconstruct_pam_case( rf, c, @@ -70,7 +70,7 @@ function _run_pam_multirealization( cfg::PAMConfig; n_realizations::Int, source_phase_mode::Symbol, - use_gpu::Bool, + kwave_use_gpu::Bool, rng::Random.AbstractRNG, recon_kwargs::NamedTuple, ) @@ -81,7 +81,7 @@ function _run_pam_multirealization( for _ in 1:n_realizations resampled = _resample_source_phases(sources, rng) - rf, kgrid, sim_info = simulate_point_sources(c, rho, resampled, cfg; use_gpu=use_gpu) + rf, kgrid, sim_info = simulate_point_sources(c, rho, resampled, cfg; use_gpu=kwave_use_gpu) results = reconstruct_pam_case(rf, c, resampled, cfg; simulation_info=sim_info, recon_kwargs...) if isnothing(geo_acc) geo_acc = Float64.(results[:pam_geo]) @@ -110,6 +110,7 @@ function run_pam_case( frequencies::Union{Nothing, AbstractVector{<:Real}}=nothing, bandwidth::Real=0.0, use_gpu::Bool=false, + kwave_use_gpu::Bool=false, analysis_mode::Symbol=:localization, peak_method::Symbol=:argmax, clean_loop_gain::Real=0.1, @@ -161,7 +162,7 @@ function run_pam_case( c, rho, effective_sources, cfg; n_realizations=n_realizations, source_phase_mode=phase_mode, - use_gpu=use_gpu, + kwave_use_gpu=kwave_use_gpu, rng=rng, recon_kwargs=recon_kwargs, ) @@ -169,13 +170,13 @@ function run_pam_case( return _run_pam_per_window( c, rho, effective_sources, cfg; source_phase_mode=phase_mode, - use_gpu=use_gpu, + kwave_use_gpu=kwave_use_gpu, rng=rng, recon_kwargs=recon_kwargs, variability=source_variability, ) end - rf, kgrid, sim_info = simulate_point_sources(c, rho, effective_sources, cfg; use_gpu=use_gpu) + rf, kgrid, sim_info = simulate_point_sources(c, rho, effective_sources, cfg; use_gpu=kwave_use_gpu) results = reconstruct_pam_case(rf, c, effective_sources, cfg; simulation_info=sim_info, recon_kwargs...) results[:kgrid] = kgrid results[:source_phase_mode] = phase_mode diff --git a/validation/2D_PAM_Accuracy/plot_results.jl b/validation/2D_PAM_Accuracy/plot_results.jl new file mode 100644 index 0000000..89a003f --- /dev/null +++ b/validation/2D_PAM_Accuracy/plot_results.jl @@ -0,0 +1,273 @@ +""" +Reproduce Fig. 7 of Schoen & Arvanitis (2020) from saved validation results. + +Usage: + julia --project=. validation/2D_PAM_Accuracy/plot_results.jl [results_file.jld2] +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using CairoMakie, JLD2, TranscranialFUS, Statistics, Printf + +# ── Load results ────────────────────────────────────────────────────────────── + +results_dir = @__DIR__ +results_file = if !isempty(ARGS) + ARGS[1] +else + files = filter(f -> startswith(f, "results_") && endswith(f, ".jld2"), readdir(results_dir)) + isempty(files) && error("No results_*.jld2 in $results_dir. Run run_validation.jl first.") + joinpath(results_dir, last(sort(files))) +end +println("Loading: $results_file") + +d = load(results_file) +geo_errors_mm = d["geo_errors_mm"] +hasa_errors_mm = d["hasa_errors_mm"] +AXIAL_MM = d["AXIAL_MM"] +LATERAL_MM = d["LATERAL_MM"] +APERTURES_MM = d["APERTURES_MM"] +DX = d["DX"] +DT = d["DT"] +T_MAX = d["T_MAX"] +AXIAL_DIM = d["AXIAL_DIM"] +TRANS_DIM = d["TRANS_DIM"] +SKULL_DIST = d["SKULL_DIST"] +SLICE_INDEX = d["SLICE_INDEX"] + +# ── Rebuild medium for panel (a) ────────────────────────────────────────────── + +MAX_APT_MM = maximum(APERTURES_MM) +sim_cfg = PAMConfig( + dx = DX, + dz = DX, + axial_dim = AXIAL_DIM, + transverse_dim = TRANS_DIM, + receiver_aperture = MAX_APT_MM * 1e-3, + t_max = T_MAX, + dt = DT, +) + +println("Rebuilding skull medium…") +c, _, _ = make_pam_medium( + sim_cfg; + aberrator = :skull, + skull_to_transducer = SKULL_DIST, + slice_index = SLICE_INDEX, +) + +# ── Coordinate arrays ───────────────────────────────────────────────────────── + +Nx, Ny = size(c) +R = receiver_row(sim_cfg) +dx_mm = DX * 1e3 + +ax_coords = [(i - R) * dx_mm for i in 1:Nx] +lat_coords = [(j - (Ny ÷ 2 + 1)) * dx_mm for j in 1:Ny] + +# ── Aperture colours (100→red, 75→green, 50→teal) ──────────────────────────── + +apt_colors = Dict( + 100.0 => RGBf(0.80, 0.20, 0.15), + 75.0 => RGBf(0.15, 0.60, 0.15), + 50.0 => RGBf(0.10, 0.65, 0.70), +) + +# ── Error colour / size helpers ─────────────────────────────────────────────── + +MAX_ERR = 8.0 +MIN_MS = 2.5 +MAX_MS = 15.0 +errcmap = :plasma + +err_to_ms(e) = MIN_MS + (MAX_MS - MIN_MS) * clamp(e, 0.0, MAX_ERR) / MAX_ERR + +function plot_error_grid!(ax, errors_pi, axial_mm, lateral_mm) + for (ai, az) in enumerate(axial_mm), (li, lat) in enumerate(lateral_mm) + e = errors_pi[ai, li] + isnan(e) && continue + scatter!(ax, [lat], [az]; + color = clamp(e, 0.0, MAX_ERR), + colorrange = (0.0, MAX_ERR), + colormap = errcmap, + markersize = err_to_ms(e), + strokewidth = 0, + ) + end +end + +ax_lim_dep = (maximum(AXIAL_MM) + 5.0, minimum(AXIAL_MM) - 5.0) # yreversed order + +# ── Theme ───────────────────────────────────────────────────────────────────── + +update_theme!( + fontsize = 9, + Axis = ( + xgridvisible = false, + ygridvisible = false, + topspinevisible = false, + rightspinevisible = false, + ), +) + +fig = Figure(size = (920, 420)) + +# ── Panel (a): skull with source grid ──────────────────────────────────────── + +# Visible depth range: just above skull to deepest source +depth_top_mm = SKULL_DIST * 1e3 - 8.0 # a bit above the skull +depth_bot_mm = maximum(AXIAL_MM) + 5.0 + +# Bar y-coords (above skull, negative depth = between receiver and skull) +bar_bot_mm = depth_top_mm - 6.0 +bar_top_mm = depth_top_mm - 2.5 +bar_mid_mm = (bar_bot_mm + bar_top_mm) / 2.0 + +ax_a = Axis(fig[1:2, 1]; + xlabel = "Transverse Position [mm]", + ylabel = "Axial Position [mm]", + aspect = DataAspect(), + yreversed = true, + title = "a", + titlealign = :left, + titlefont = :bold, +) + +# Skull sound-speed heatmap +heatmap!(ax_a, lat_coords, ax_coords, c'; + colormap = :grays, + colorrange = (1400, 2100), +) + +# Source dots +for az in AXIAL_MM, lat in LATERAL_MM + scatter!(ax_a, [lat], [az]; color = :black, markersize = 4) +end + +# Aperture bars: widest drawn first so narrower bars sit on top +for apt_mm in sort(APERTURES_MM; rev=true) + half_mm = apt_mm / 2.0 + band!(ax_a, [-half_mm, half_mm], bar_bot_mm, bar_top_mm; + color = (apt_colors[apt_mm], 0.9)) +end + +# Labels: placed visually above the bars (smaller y = higher with yreversed) +# bar_bot_mm is the visual top of the bar; go further up (smaller y) +label_y = bar_bot_mm - 2.5 +# Place each label in its bar's exclusive outer zone (half-widths: 50, 37.5, 25 mm) +label_xs = [48.0, 31.0, 0.0] # 100 mm → outer wing; 75 mm → mid ring; 50 mm → centre +for (xi, apt_mm) in zip(label_xs, sort(APERTURES_MM; rev=true)) + text!(ax_a, xi, label_y; + text = "$(round(Int, apt_mm)) mm", + align = (:center, :center), + color = apt_colors[apt_mm], + fontsize = 7, + font = :bold, + ) +end + +xlims!(ax_a, -56.0, 56.0) +ylims!(ax_a, depth_bot_mm, label_y - 1.5) # yreversed: first=visual bottom + +# Sound-speed colorbar: small horizontal strip above panel (a) +Colorbar(fig[0, 1]; + colormap = :grays, + colorrange = (1400, 2100), + label = "Sound Speed [m/s]", + vertical = false, + height = 10, + ticklabelsize = 7, + labelsize = 8, + ticks = [1400, 1700, 2100], + tellwidth = false, +) + +# ── Panels (b) and (c) ──────────────────────────────────────────────────────── + +for (pi, apt_mm) in enumerate(APERTURES_MM) + tcol = apt_colors[apt_mm] + gcol = pi + 1 # figure columns 2..4 + + show_xlabel = pi == 2 + show_ylabel_b = pi == 1 + show_ylabel_c = pi == 1 + + # ---- b: uncorrected ---- + ax_b = Axis(fig[1, gcol]; + xlabel = show_xlabel ? "Transverse Position [mm]" : "", + ylabel = show_ylabel_b ? "Axial Position [mm]" : "", + yreversed = true, + aspect = DataAspect(), + title = "$(round(Int, apt_mm)) mm", + titlecolor = tcol, + xticklabelsize = 7, + yticklabelsize = 7, + ) + plot_error_grid!(ax_b, geo_errors_mm[pi, :, :], AXIAL_MM, LATERAL_MM) + xlims!(ax_b, -25.0, 25.0) + ylims!(ax_b, ax_lim_dep...) + + # ---- c: corrected ---- + ax_c = Axis(fig[2, gcol]; + xlabel = show_xlabel ? "Transverse Position [mm]" : "", + ylabel = show_ylabel_c ? "Axial Position [mm]" : "", + yreversed = true, + aspect = DataAspect(), + xticklabelsize = 7, + yticklabelsize = 7, + ) + plot_error_grid!(ax_c, hasa_errors_mm[pi, :, :], AXIAL_MM, LATERAL_MM) + xlims!(ax_c, -25.0, 25.0) + ylims!(ax_c, ax_lim_dep...) +end + +Label(fig[0, 2:4], "Uncorrected"; + fontsize = 11, font = :bold, + color = RGBf(0.45, 0.0, 0.55), + halign = :center, + valign = :bottom, + padding = (0, 0, 0, 4), +) +Label(fig[2, 2:4, Top()], "Corrected"; + fontsize = 11, font = :bold, + color = RGBf(0.70, 0.30, 0.05), + halign = :center, + padding = (0, 0, 6, 0), +) + +# ── Shared error colorbar ───────────────────────────────────────────────────── + +Colorbar(fig[1:2, 5]; + colormap = errcmap, + colorrange = (0.0, MAX_ERR), + label = "Error [mm]", + ticklabelsize = 7, + labelsize = 8, + width = 12, + ticks = 0:2:Int(MAX_ERR), +) + +# ── Spacing ─────────────────────────────────────────────────────────────────── + +colgap!(fig.layout, 5) +rowgap!(fig.layout, 3) + +# ── Print table ─────────────────────────────────────────────────────────────── + +println() +println(" Aperture │ Geo (uncorrected) │ HASA (corrected) │ Paper HASA") +println(" ─────────┼──────────────────────┼───────────────────────┼────────────────") +ref = Dict(50.0=>"1.2 ± 0.7", 75.0=>"0.9 ± 0.5", 100.0=>"0.8 ± 0.4") +for (pi, apt_mm) in enumerate(APERTURES_MM) + gv = filter(!isnan, geo_errors_mm[pi, :, :]) + hv = filter(!isnan, hasa_errors_mm[pi, :, :]) + @printf(" %3.0f mm │ %4.1f ± %4.1f mm │ %4.1f ± %4.1f mm │ %s mm\n", + apt_mm, mean(gv), std(gv), mean(hv), std(hv), ref[apt_mm]) +end + +# ── Save ────────────────────────────────────────────────────────────────────── + +outfile = replace(results_file, r"\.jld2$" => "_fig7.pdf") +save(outfile, fig) +println("\nSaved → $outfile") diff --git a/validation/2D_PAM_Accuracy/results.md b/validation/2D_PAM_Accuracy/results.md new file mode 100644 index 0000000..ba4cb51 --- /dev/null +++ b/validation/2D_PAM_Accuracy/results.md @@ -0,0 +1,16 @@ +# 2D PAM Localization Accuracy — Schoen & Arvanitis (2020) Reproduction + +**Setup:** 54 point sources (6 axial × 9 lateral, 30–80 mm depth, ±20 mm lateral), +simulated through a human skull CT slice (slice 250, skull at 20 mm) with k-Wave. +Frequency: 1 MHz, 10 cycles. Grid: 200 µm pitch, 40 ns time step. +Reconstructed with homogeneous ASA (geometric) and heterogeneous ASA (HASA, Eq. 6). + +| Aperture | Geo (uncorrected) | HASA (corrected) | Paper HASA (Table II) | +|----------|--------------------|-------------------|-----------------------| +| 50 mm | 10.1 ± 8.6 mm | 1.1 ± 1.1 mm | 1.2 ± 0.7 mm | +| 75 mm | 6.9 ± 6.0 mm | 0.7 ± 0.5 mm | 0.9 ± 0.5 mm | +| 100 mm | 5.4 ± 4.8 mm | 0.6 ± 0.4 mm | 0.8 ± 0.4 mm | + +HASA errors are within ~0.2 mm of the paper across all apertures. +Geometric errors are larger than the paper (3.7/2.5/3.5 mm), consistent with using a +single CT slice rather than an average over many skull positions. diff --git a/validation/2D_PAM_Accuracy/results_20260509_114048_fig7.pdf b/validation/2D_PAM_Accuracy/results_20260509_114048_fig7.pdf new file mode 100644 index 0000000000000000000000000000000000000000..1d178bdd4c868e1f28dd9b0786c7cada4b5c3153 GIT binary patch literal 1009745 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The PAM is reconstructed with +the homogeneous ASA (geometric) and the heterogeneous ASA (HASA, Eq. 6). +Localization errors are tabulated for three receiver apertures (50, 75, 100 mm). + +Each source is simulated once with the largest aperture; smaller apertures are +obtained by zeroing RF outside the requested element range, so reconstruction +is free. + +Run from the project root: + julia --project=. validation/2D_PAM_Accuracy/run_validation.jl [--recon-use-gpu] +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using TranscranialFUS +using Statistics, JLD2, Printf, Dates + +# ── Configuration ────────────────────────────────────────────────────────────── + +# Grid (matching paper: 200 µm pitch, 40 ns time step) +const DX = 0.2e-3 # m – axial and lateral spacing +const DT = 40e-9 # s +const T_MAX = 100e-6 # s – covers 80 mm source + full 100 mm aperture +const AXIAL_DIM = 100e-3 # m – total axial extent (skull at 20 mm, sources ≤ 80 mm) +const SKULL_DIST = 20e-3 # m – outer skull surface below receiver +const SLICE_INDEX = 250 # CT slice (same default as run_pam.jl) + +# Source grid (paper: 30–80 mm axial, ±20 mm lateral, 1 MHz) +const FREQ = 1.0e6 # Hz +const NUM_CYCLES = 10 # source duration = 10 µs at 1 MHz +const AXIAL_MM = [30.0, 40.0, 50.0, 60.0, 70.0, 80.0] # mm +const LATERAL_MM = [-20.0, -15.0, -10.0, -5.0, 0.0, 5.0, 10.0, 15.0, 20.0] # mm + +# Apertures to sweep (paper Fig. 7: 50, 75, 100 mm) +const APERTURES_MM = [50.0, 75.0, 100.0] +const MAX_APT_MM = maximum(APERTURES_MM) + +# Reconstruction +const AXIAL_STEP = 50e-6 # m – Δz in HASA marching (matches paper) +const BANDWIDTH = 0.0 # Hz – exact bin (no smoothing) + +# k-Wave simulation always uses GPU. +# PAM reconstruction uses GPU only when --recon-use-gpu is passed. +const USE_GPU_RECON = "--recon-use-gpu" in ARGS + +# ── Domain and medium ────────────────────────────────────────────────────────── + +# Transverse domain must fit the largest aperture plus PML guard. +# PML guard at DX = 0.2 mm: default is max(4, round(4 mm / DX)) = 20 cells = 4 mm. +# Use 12 mm margin on each side → total = MAX_APT_MM + 24 mm. +const TRANS_DIM = (MAX_APT_MM + 24.0) * 1e-3 + +sim_cfg = PAMConfig( + dx = DX, + dz = DX, + axial_dim = AXIAL_DIM, + transverse_dim = TRANS_DIM, + receiver_aperture = MAX_APT_MM * 1e-3, + t_max = T_MAX, + dt = DT, +) + +println("Domain: $(round(Int, AXIAL_DIM*1e3)) mm axial × $(round(Int, TRANS_DIM*1e3)) mm lateral") +println("Grid : $(pam_Nx(sim_cfg)) × $(pam_Ny(sim_cfg)) cells, Nt = $(pam_Nt(sim_cfg))") +println("Active receiver: $(round(Int, MAX_APT_MM)) mm ($(round(Int, MAX_APT_MM*1e-3/DX)) elements)") +println() + +println("Building skull medium (CT slice $SLICE_INDEX, skull at $(round(Int,SKULL_DIST*1e3)) mm)…") +c, rho, med_info = make_pam_medium( + sim_cfg; + aberrator = :skull, + skull_to_transducer = SKULL_DIST, + slice_index = SLICE_INDEX, +) +println(" outer skull row : $(med_info[:outer_row])") +println(" inner skull row : $(med_info[:inner_row])") +println(" c₀ (water) : $(sim_cfg.c0) m/s") +println() + +# ── Sweep storage ───────────────────────────────────────────────────────────── + +n_ax = length(AXIAL_MM) +n_lat = length(LATERAL_MM) +n_apt = length(APERTURES_MM) +n_total = n_ax * n_lat + +# Shape: [n_apt × n_ax × n_lat] +geo_errors_mm = fill(NaN, n_apt, n_ax, n_lat) +hasa_errors_mm = fill(NaN, n_apt, n_ax, n_lat) +geo_ax_err_mm = fill(NaN, n_apt, n_ax, n_lat) +hasa_ax_err_mm = fill(NaN, n_apt, n_ax, n_lat) +geo_lat_err_mm = fill(NaN, n_apt, n_ax, n_lat) +hasa_lat_err_mm = fill(NaN, n_apt, n_ax, n_lat) + +ny = pam_Ny(sim_cfg) +mid_col = ny ÷ 2 + 1 # center column index + +# Pre-compute active column ranges for each aperture. +# Use start = mid - floor(n/2), end = start + n - 1 so the range always has +# exactly n_elem columns regardless of odd/even. +apt_ranges = Dict{Float64, UnitRange{Int}}() +for apt_mm in APERTURES_MM + n_elem = round(Int, apt_mm * 1e-3 / DX) + half = n_elem ÷ 2 # floor division + astart = mid_col - half + aend = astart + n_elem - 1 + (1 <= astart && aend <= ny) || + error("Aperture $(apt_mm) mm exceeds transverse domain $(round(Int, TRANS_DIM*1e3)) mm.") + apt_ranges[apt_mm] = astart:aend +end + +# ── Main sweep ──────────────────────────────────────────────────────────────── + +t_sweep_start = time() +s_count = 0 + +for (ai, ax_mm) in enumerate(AXIAL_MM), (li, lat_mm) in enumerate(LATERAL_MM) + global s_count += 1 + elapsed = time() - t_sweep_start + eta_s = s_count > 1 ? elapsed / (s_count - 1) * (n_total - s_count + 1) : NaN + eta_str = isnan(eta_s) ? "?" : @sprintf("%.0f", eta_s / 60) + @printf("[%2d/%d] ax=%4.0fmm lat=%+5.0fmm (ETA ~%s min)\n", + s_count, n_total, ax_mm, lat_mm, eta_str) + + src = PointSource2D( + depth = ax_mm * 1e-3, + lateral = lat_mm * 1e-3, + frequency = FREQ, + num_cycles = NUM_CYCLES, + ) + + # Simulate once with full (MAX_APT_MM) aperture + rf_full, kgrid, _ = simulate_point_sources(c, rho, [src], sim_cfg; use_gpu=true) + + for (pi, apt_mm) in enumerate(APERTURES_MM) + # Mask RF to requested aperture by zeroing outside active range + apt_range = apt_ranges[apt_mm] + rf_apt = zeros(Float64, ny, size(rf_full, 2)) + rf_apt[apt_range, :] .= rf_full[apt_range, :] + + # Reconstruct: homogeneous ASA (geo) and heterogeneous ASA (HASA) + pam_geo, _, _ = reconstruct_pam(rf_apt, c, sim_cfg; + corrected = false, + frequencies = [FREQ], + bandwidth = BANDWIDTH, + axial_step = AXIAL_STEP, + use_gpu = USE_GPU_RECON, # --recon-use-gpu flag + ) + pam_hasa, _, _ = reconstruct_pam(rf_apt, c, sim_cfg; + corrected = true, + frequencies = [FREQ], + bandwidth = BANDWIDTH, + axial_step = AXIAL_STEP, + use_gpu = USE_GPU_RECON, # --recon-use-gpu flag + ) + + # Localization error via existing analysis function (1 source → argmax) + stats_geo = analyse_pam_2d(pam_geo, kgrid, sim_cfg, [src]) + stats_hasa = analyse_pam_2d(pam_hasa, kgrid, sim_cfg, [src]) + + geo_errors_mm[pi, ai, li] = only(stats_geo[:radial_errors_mm]) + hasa_errors_mm[pi, ai, li] = only(stats_hasa[:radial_errors_mm]) + geo_ax_err_mm[pi, ai, li] = only(stats_geo[:axial_errors_mm]) + hasa_ax_err_mm[pi, ai, li] = only(stats_hasa[:axial_errors_mm]) + geo_lat_err_mm[pi, ai, li] = only(stats_geo[:lateral_errors_mm]) + hasa_lat_err_mm[pi, ai, li] = only(stats_hasa[:lateral_errors_mm]) + end +end + +total_time_min = (time() - t_sweep_start) / 60 +@printf("\nSweep complete in %.1f minutes.\n\n", total_time_min) + +# ── Print results (Table II format) ─────────────────────────────────────────── + +println("="^72) +println("PAM Localization Error — 2D Skull (Schoen & Arvanitis 2020, Table II)") +println("="^72) +println() +@printf(" Sources: %d axial × %d lateral = %d total\n", n_ax, n_lat, n_total) +@printf(" Frequency: %.1f MHz, Axial step: %.0f µm\n", FREQ/1e6, AXIAL_STEP*1e6) +println() + +println(" Aperture │ Uncorrected (geo) │ Corrected (HASA)") +println(" ─────────┼─────────────────────┼────────────────────") +for (pi, apt_mm) in enumerate(APERTURES_MM) + geo_vals = filter(!isnan, geo_errors_mm[pi, :, :]) + hasa_vals = filter(!isnan, hasa_errors_mm[pi, :, :]) + @printf(" %3.0f mm │ %4.1f ± %4.1f mm │ %4.1f ± %4.1f mm\n", + apt_mm, + mean(geo_vals), std(geo_vals), + mean(hasa_vals), std(hasa_vals)) +end +println() + +println(" Reference (paper, Table II):") +println(" Aperture │ Uncorrected │ Corrected") +println(" ─────────┼──────────────────────┼──────────────────────") +println(" 50 mm │ 3.7 ± 2.2 mm │ 1.2 ± 0.7 mm") +println(" 75 mm │ 2.5 ± 1.7 mm │ 0.9 ± 0.5 mm") +println(" 100 mm │ 3.5 ± 1.9 mm │ 0.8 ± 0.4 mm") +println() + +println(" Per-aperture breakdown (mean |axial| / |lateral| error):") +println(" Aperture │ Method │ |Axial| mm │ |Lateral| mm") +println(" ─────────┼────────┼──────────────┼─────────────") +for (pi, apt_mm) in enumerate(APERTURES_MM) + for (method, ax_err, lat_err) in [ + ("geo ", geo_ax_err_mm, geo_lat_err_mm), + ("hasa", hasa_ax_err_mm, hasa_lat_err_mm), + ] + ax_vals = filter(!isnan, abs.(ax_err[pi, :, :])) + lat_vals = filter(!isnan, abs.(lat_err[pi, :, :])) + @printf(" %3.0f mm │ %-6s │ %5.2f ± %4.2f │ %5.2f ± %4.2f\n", + apt_mm, method, mean(ax_vals), std(ax_vals), mean(lat_vals), std(lat_vals)) + end +end +println() + +# ── Save results ────────────────────────────────────────────────────────────── + +outdir = @__DIR__ +ts = Dates.format(now(), "yyyymmdd_HHMMSS") +outfile = joinpath(outdir, "results_$(ts).jld2") + +jldsave(outfile; + geo_errors_mm, hasa_errors_mm, + geo_ax_err_mm, hasa_ax_err_mm, + geo_lat_err_mm, hasa_lat_err_mm, + AXIAL_MM, LATERAL_MM, APERTURES_MM, + FREQ, AXIAL_STEP, DX, DT, T_MAX, + AXIAL_DIM, TRANS_DIM, SKULL_DIST, SLICE_INDEX, + med_info, + total_time_min, +) +println("Results saved → $outfile") From 29d280911b0b157e4e46c30e4bb7c0d7c01e0db0 Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 13:46:57 +0200 Subject: [PATCH 02/19] 3d cpu hasa for performance comparison --- src/pam/reconstruction3d.jl | 172 +++++++++++++-- validation/3D_PAM_Accuracy/plot_results.jl | 216 ++++++++++++++++++ validation/3D_PAM_Accuracy/results.md | 3 + validation/3D_PAM_Accuracy/run_validation.jl | 217 +++++++++++++++++++ 4 files changed, 594 insertions(+), 14 deletions(-) create mode 100644 validation/3D_PAM_Accuracy/plot_results.jl create mode 100644 validation/3D_PAM_Accuracy/results.md create mode 100644 validation/3D_PAM_Accuracy/run_validation.jl diff --git a/src/pam/reconstruction3d.jl b/src/pam/reconstruction3d.jl index 08771b8..3d74803 100644 --- a/src/pam/reconstruction3d.jl +++ b/src/pam/reconstruction3d.jl @@ -435,6 +435,142 @@ function _reconstruct_pam_cuda_3d( return raws, timing end +function _reconstruct_pam_cpu_3d( + c_padded::AbstractArray{<:Real, 3}, + rf::AbstractArray{<:Real, 3}, + cfg::PAMConfig3D, + selected_freqs::AbstractVector{<:Real}, + selected_bins::AbstractVector{<:Integer}, + crop_range_y::UnitRange{Int}, + crop_range_z::UnitRange{Int}, + padded_ny::Int, + padded_nz::Int, + rr::Int, + row_stop::Int, + c0::Float64, + effective_axial_step::Float64, + axial_substeps::Int, + corrected::Bool, + t0::Float64, + recon_label::AbstractString, + show_progress::Bool, +) + t_setup_start = time() + nx = size(c_padded, 1) + crop_ny = length(crop_range_y) + crop_nz = length(crop_range_z) + crop_y0 = first(crop_range_y) + crop_z0 = first(crop_range_z) + nfreq = length(selected_freqs) + + # Sound-speed contrast field: (padded_ny, padded_nz, nx), matching GPU eta layout + eta_spatial = permutedims(Float64.(1.0 .- (c0 ./ c_padded) .^ 2), (2, 3, 1)) + + k_y = _fft_wavenumbers(padded_ny, cfg.dy) + k_z = _fft_wavenumbers(padded_nz, cfg.dz) + k_lat2 = reshape(k_y, :, 1) .^ 2 .+ reshape(k_z, 1, :) .^ 2 + k_radii = sqrt.(k_lat2) + + # Pre-plan FFTW once for the padded lateral plane; MEASURE finds the optimal kernel + dummy = zeros(ComplexF64, padded_ny, padded_nz) + plan_fwd = plan_fft(dummy, (1, 2); flags=FFTW.MEASURE) + plan_bwd = plan_ifft(dummy, (1, 2); flags=FFTW.MEASURE) + + rf_fft = fft(Float64.(rf), 3) # time FFT: (ny, nz, nt) + t_setup_s = time() - t_setup_start + + intensity = zeros(Float64, nx, crop_ny, crop_nz) + + println("[ PAM 3D ] $recon_label: CPU (single-threaded FFTW, MEASURE), $nfreq freq bins") + flush(stdout) + + march_wall_start = time() + + for (freq, bin) in zip(selected_freqs, selected_bins) + k0 = 2π * freq / c0 + k0_sq = k0^2 + + k_axial = sqrt.(complex.(k0^2 .- k_lat2, 0.0)) + propagating = real.(k_axial ./ k0) .> 0.0 + propagator = exp.(1im .* k_axial .* effective_axial_step) .* propagating + + k_max_prop = maximum(k_radii[propagating]; init=0.0) + weighting = _tukey_radial(k_radii, k_max_prop, cfg.tukey_ratio) .* propagating + + correction = zeros(ComplexF64, padded_ny, padded_nz) + if corrected + for j in eachindex(k_axial) + propagating[j] || continue + abs(k_axial[j]) > sqrt(eps(Float64)) || continue + correction[j] = propagator[j] * effective_axial_step / (2im * k_axial[j]) + end + end + + # Apply ifftshift to match GPU FFT convention + prop_shifted = _ifftshift_2d(propagating .* propagator) + weight_shifted = _ifftshift_2d(weighting) + prop_n_weight = _ifftshift_2d(propagating .* propagator .^ axial_substeps .* weighting) + prop_w = corrected ? prop_shifted .* weight_shifted : nothing + corr_w = corrected ? _ifftshift_2d(propagating .* correction) .* weight_shifted : nothing + + # Initial condition: place RF frequency slice into padded array + phase = cis(-2π * freq * t0) + p0 = zeros(ComplexF64, padded_ny, padded_nz) + p0[crop_range_y, crop_range_z] .= rf_fft[:, :, bin] .* phase + current = plan_fwd * p0 + current .*= weight_shifted + + for row in (rr + 1):row_stop + if corrected + eta_slice = @view eta_spatial[:, :, row] + for _ in 1:(axial_substeps - 1) + p_spatial = plan_bwd * current + lp_fft = plan_fwd * (k0_sq .* eta_slice .* p_spatial) + current = current .* prop_w .+ corr_w .* lp_fft + end + p_spatial = plan_bwd * current + lp_fft = plan_fwd * (k0_sq .* eta_slice .* p_spatial) + current = current .* prop_w .+ corr_w .* lp_fft + else + current .*= prop_n_weight + end + p_row = plan_bwd * current + for iz in 1:crop_nz, iy in 1:crop_ny + v = p_row[crop_y0 + iy - 1, crop_z0 + iz - 1] + intensity[row, iy, iz] += real(v)^2 + imag(v)^2 + end + end + end + + march_wall_s = time() - march_wall_start + + _pam_progress( + show_progress, + "PAM 3D $recon_label CPU: march $(round(march_wall_s; digits=1)) s, $nfreq freq bins", + ) + + timing = Dict{Symbol, Any}( + :setup_s => t_setup_s, + :operator_setup_s => t_setup_s, + :batch_setup_s => 0.0, + :march_wall_s => march_wall_s, + :march_cpu_s => march_wall_s, + :march_gpu_s => nothing, + :download_s => 0.0, + :bandwidth_GBps => nothing, + :fft_s => nothing, + :elementwise_s => nothing, + :nrows => row_stop - rr, + :nfreq => nfreq, + :nwindows => 1, + :padded_ny => padded_ny, + :padded_nz => padded_nz, + :axial_substeps => axial_substeps, + :bytes_march_est => nothing, + ) + return [intensity], timing +end + function reconstruct_pam_3d( rf::AbstractArray{<:Real, 3}, c::AbstractArray{<:Real, 3}, @@ -455,7 +591,6 @@ function reconstruct_pam_3d( nx, ny, nz = size(c) size(rf, 1) == ny && size(rf, 2) == nz || error("RF data must have size (ny, nz, nt); expected ($ny, $nz, ·), got ($(size(rf,1)), $(size(rf,2)), ·).") - nt = size(rf, 3) rr = receiver_row(cfg) rr <= nx || error("Receiver row lies outside the computational grid.") @@ -482,17 +617,26 @@ function reconstruct_pam_3d( "grid=$(nx)×$(ny)×$(nz), padded=($(padded_ny)×$(padded_nz)), substeps=$axial_substeps", ) - use_gpu || error("CPU path not implemented for 3D PAM; use use_gpu=true.") - - setup = _pam_cuda_setup_3d( - c_padded, cfg, selected_freqs, selected_bins, - crop_range_y, crop_range_z, - nx, padded_ny, padded_nz, rr, row_stop, - c0, effective_axial_step, axial_substeps, - ) - raws, gpu_timing = _reconstruct_pam_cuda_3d( - setup, [rf], [t0], corrected, recon_label, show_progress, benchmark, - ) + raws, gpu_timing = if use_gpu + setup = _pam_cuda_setup_3d( + c_padded, cfg, selected_freqs, selected_bins, + crop_range_y, crop_range_z, + nx, padded_ny, padded_nz, rr, row_stop, + c0, effective_axial_step, axial_substeps, + ) + _reconstruct_pam_cuda_3d( + setup, [rf], [t0], corrected, recon_label, show_progress, benchmark, + ) + else + _reconstruct_pam_cpu_3d( + c_padded, rf, cfg, + selected_freqs, selected_bins, + crop_range_y, crop_range_z, + padded_ny, padded_nz, rr, row_stop, + c0, effective_axial_step, axial_substeps, + corrected, t0, recon_label, show_progress, + ) + end intensity = raws[1] # (nx, ny, nz) _apply_axial_gain_3d!(intensity, cfg) @@ -510,8 +654,8 @@ function reconstruct_pam_3d( :axial_substeps_per_cell => axial_substeps, :time_origin => t0, :use_gpu => use_gpu, - :backend => :cuda, - :gpu_precision => _PAM_CUDA_PRECISION, + :backend => use_gpu ? :cuda : :cpu, + :gpu_precision => use_gpu ? _PAM_CUDA_PRECISION : nothing, :axial_gain_power => cfg.axial_gain_power, :show_progress => show_progress, :benchmark => benchmark, diff --git a/validation/3D_PAM_Accuracy/plot_results.jl b/validation/3D_PAM_Accuracy/plot_results.jl new file mode 100644 index 0000000..23980e9 --- /dev/null +++ b/validation/3D_PAM_Accuracy/plot_results.jl @@ -0,0 +1,216 @@ +""" +Plot 3D PAM localization accuracy from saved validation results. + +Produces a two-panel Axis3 figure: left = geometric ASA, right = HASA. +Each of the 27 sources is shown as a scatter point at its true 3D position. +Dot colour and size encode the radial localization error. +The skull cross-section (y-z plane at x = SKULL_DIST) is overlaid as a +semi-transparent heatmap slice for spatial context. + +Usage: + julia --project=. validation/3D_PAM_Accuracy/plot_results.jl [results_file.jld2] +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using CairoMakie, JLD2, TranscranialFUS, Statistics, Printf + +# ── Load results ────────────────────────────────────────────────────────────── + +results_dir = @__DIR__ +results_file = if !isempty(ARGS) + ARGS[1] +else + files = filter(f -> startswith(f, "results_") && endswith(f, ".jld2"), readdir(results_dir)) + isempty(files) && error("No results_*.jld2 in $results_dir. Run run_validation.jl first.") + joinpath(results_dir, last(sort(files))) +end +println("Loading: $results_file") + +d = load(results_file) +geo_errors_mm = d["geo_errors_mm"] +hasa_errors_mm = d["hasa_errors_mm"] +AXIAL_MM = d["AXIAL_MM"] +LATERAL_Y_MM = d["LATERAL_Y_MM"] +LATERAL_Z_MM = d["LATERAL_Z_MM"] +APERTURE_MM = d["APERTURE_MM"] +FREQ = d["FREQ"] +DX = d["DX"] +DT = d["DT"] +T_MAX = d["T_MAX"] +AXIAL_DIM = d["AXIAL_DIM"] +TRANS_DIM = d["TRANS_DIM"] +SKULL_DIST = d["SKULL_DIST"] +SLICE_INDEX = d["SLICE_INDEX"] + +# ── Print summary table ─────────────────────────────────────────────────────── + +geo_all = filter(!isnan, geo_errors_mm) +hasa_all = filter(!isnan, hasa_errors_mm) +println() +println(" Method │ Mean ± Std error") +println(" ──────────────┼──────────────────────") +@printf(" Geometric ASA │ %.2f ± %.2f mm (n=%d)\n", mean(geo_all), std(geo_all), length(geo_all)) +@printf(" HASA │ %.2f ± %.2f mm (n=%d)\n", mean(hasa_all), std(hasa_all), length(hasa_all)) +println() + +# ── Rebuild skull medium for background slice ───────────────────────────────── + +sim_cfg = PAMConfig3D( + dx = DX, + dy = DX, + dz = DX, + axial_dim = AXIAL_DIM, + transverse_dim_y = TRANS_DIM, + transverse_dim_z = TRANS_DIM, + dt = DT, + t_max = T_MAX, + receiver_aperture_y = APERTURE_MM * 1e-3, + receiver_aperture_z = APERTURE_MM * 1e-3, +) +println("Rebuilding skull medium for background slice…") +c, _, _ = make_pam_medium_3d( + sim_cfg; + aberrator = :skull, + skull_to_transducer = SKULL_DIST, + slice_index_z = SLICE_INDEX, +) + +# ── Coordinate arrays ───────────────────────────────────────────────────────── + +rr = receiver_row(sim_cfg) +dx_mm = DX * 1e3 +Ny = pam_Ny(sim_cfg) +Nz = pam_Nz(sim_cfg) +ax_coords = [(i - rr) * dx_mm for i in 1:pam_Nx(sim_cfg)] +y_coords = [(j - (Ny ÷ 2 + 1)) * dx_mm for j in 1:Ny] +z_coords = [(k - (Nz ÷ 2 + 1)) * dx_mm for k in 1:Nz] + +# Skull cross-section at the outer skull face depth +skull_depth_mm = SKULL_DIST * 1e3 +skull_row_idx = argmin(abs.(ax_coords .- skull_depth_mm)) +skull_slice_c = c[skull_row_idx, :, :] # (Ny, Nz) sound-speed map + +# ── Error → visual encoding ─────────────────────────────────────────────────── + +MAX_ERR = 6.0 +MIN_MS = 6.0 +MAX_MS = 24.0 +errcmap = :plasma + +err_to_ms(e) = MIN_MS + (MAX_MS - MIN_MS) * clamp(e, 0.0, MAX_ERR) / MAX_ERR + +# ── Figure ──────────────────────────────────────────────────────────────────── + +update_theme!(fontsize = 9) + +fig = Figure(size = (900, 440)) + +panels = [ + ("Geometric ASA", geo_errors_mm), + ("HASA", hasa_errors_mm), +] + +for (panel_col, (panel_label, errors)) in enumerate(panels) + ax = Axis3(fig[1, panel_col]; + xlabel = "Depth [mm]", + ylabel = "Lateral Y [mm]", + zlabel = "Lateral Z [mm]", + title = panel_label, + aspect = :data, + perspectiveness = 0.3, + azimuth = 5π / 8, + elevation = π / 10, + ) + + # Semi-transparent skull slice at the skull depth + surface!(ax, + fill(skull_depth_mm, Ny, Nz), + repeat(y_coords, 1, Nz), + repeat(reshape(z_coords, 1, Nz), Ny, 1); + color = Float32.(skull_slice_c), + colormap = :grays, + colorrange = (1400.0f0, 2100.0f0), + alpha = 0.35, + shading = NoShading, + ) + + # Source scatter: collect all 27 points + xs = Float64[]; ys = Float64[]; zs = Float64[] + cs = Float64[]; ms = Float64[] + for (ai, ax_mm) in enumerate(AXIAL_MM), + (yi, ly_mm) in enumerate(LATERAL_Y_MM), + (zi, lz_mm) in enumerate(LATERAL_Z_MM) + e = errors[ai, yi, zi] + isnan(e) && continue + push!(xs, Float64(ax_mm)) + push!(ys, Float64(ly_mm)) + push!(zs, Float64(lz_mm)) + push!(cs, clamp(e, 0.0, MAX_ERR)) + push!(ms, err_to_ms(e)) + end + + scatter!(ax, xs, ys, zs; + color = cs, + colorrange = (0.0, MAX_ERR), + colormap = errcmap, + markersize = ms, + strokewidth = 0.5, + strokecolor = :black, + ) + + # Receiver aperture outline at depth = 0 + half = APERTURE_MM / 2.0 + apts = [(-half, -half), (half, -half), (half, half), (-half, half), (-half, -half)] + apt_ys = [p[1] for p in apts] + apt_zs = [p[2] for p in apts] + lines!(ax, fill(0.0, 5), apt_ys, apt_zs; color = :gray50, linewidth = 0.8) +end + +# Shared error colorbar +Colorbar(fig[1, 3]; + colormap = errcmap, + colorrange = (0.0, MAX_ERR), + label = "Radial Error [mm]", + width = 14, + ticklabelsize = 8, + labelsize = 9, + ticks = 0:1:Int(MAX_ERR), +) + +colgap!(fig.layout, 8) + +# ── Save figure ─────────────────────────────────────────────────────────────── + +figfile = replace(results_file, r"\.jld2$" => "_accuracy3d.pdf") +save(figfile, fig) +println("Saved → $figfile") + +# ── Write results.md ────────────────────────────────────────────────────────── + +md_path = joinpath(results_dir, "results.md") +open(md_path, "w") do io + println(io, "# 3D PAM Accuracy Validation\n") + println(io, "**Aperture:** $(round(Int, APERTURE_MM)) mm × $(round(Int, APERTURE_MM)) mm ") + n_src = length(AXIAL_MM) * length(LATERAL_Y_MM) * length(LATERAL_Z_MM) + println(io, "**Sources:** $(length(AXIAL_MM)) axial × $(length(LATERAL_Y_MM)) y × $(length(LATERAL_Z_MM)) z = $n_src total ") + println(io, "**Frequency:** $(FREQ/1e6) MHz ") + println(io, "**Grid:** $(round(Int, DX*1e6)) µm isotropic ") + println(io, "**Skull:** CT slice $SLICE_INDEX, outer surface at $(round(Int, SKULL_DIST*1e3)) mm \n") + println(io, "| Method | Mean error | Std error | n |") + println(io, "|---------------|-----------|-----------|---|") + @printf(io, "| Geometric ASA | %.2f mm | %.2f mm | %d |\n", mean(geo_all), std(geo_all), length(geo_all)) + @printf(io, "| HASA | %.2f mm | %.2f mm | %d |\n", mean(hasa_all), std(hasa_all), length(hasa_all)) + println(io, "\n## Per-depth breakdown\n") + println(io, "| Depth | Geo mean±std | HASA mean±std |") + println(io, "|-------|----------------|----------------|") + for (ai, ax_mm) in enumerate(AXIAL_MM) + gv = filter(!isnan, geo_errors_mm[ai, :, :]) + hv = filter(!isnan, hasa_errors_mm[ai, :, :]) + @printf(io, "| %3.0f mm | %.2f ± %.2f mm | %.2f ± %.2f mm |\n", + ax_mm, mean(gv), std(gv), mean(hv), std(hv)) + end + println(io, "\n*Figure: $(basename(figfile))*") +end +println("Written → $md_path") diff --git a/validation/3D_PAM_Accuracy/results.md b/validation/3D_PAM_Accuracy/results.md new file mode 100644 index 0000000..0a9df1a --- /dev/null +++ b/validation/3D_PAM_Accuracy/results.md @@ -0,0 +1,3 @@ +# 3D PAM Accuracy Validation + +*Results not yet generated. Run `run_validation.jl` then `plot_results.jl`.* diff --git a/validation/3D_PAM_Accuracy/run_validation.jl b/validation/3D_PAM_Accuracy/run_validation.jl new file mode 100644 index 0000000..246546a --- /dev/null +++ b/validation/3D_PAM_Accuracy/run_validation.jl @@ -0,0 +1,217 @@ +""" +3D PAM localization accuracy — single fixed aperture. + +27 point sources (3 axial × 3 lateral-y × 3 lateral-z) are simulated through +a skull CT extruded to 3D with k-Wave. PAM is reconstructed with geometric +ASA and HASA for a fixed 64 mm square aperture. Radial localization errors +and GPU reconstruction timings are recorded. + +Run from the project root: + julia --project=. validation/3D_PAM_Accuracy/run_validation.jl +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using TranscranialFUS +using Statistics, JLD2, Printf, Dates + +# ── Configuration ────────────────────────────────────────────────────────────── + +const FREQ = 1.0e6 # Hz +const NUM_CYCLES = 10.0 # source duration = 10 µs at 1 MHz +const DX = 0.2e-3 # m — isotropic grid spacing +const DT = 40e-9 # s +const T_MAX = 120e-6 # s — covers deepest source + diagonal aperture path +const AXIAL_STEP = 50e-6 # m — HASA march step (matches 2D validation) +const BANDWIDTH = 0.0 # Hz — exact bin + +const SKULL_DIST = 20e-3 # m — outer skull surface to receiver +const SLICE_INDEX = 250 # CT slice (same as 2D validation) + +const APERTURE_MM = 64.0 # mm — fixed square aperture in y and z + +# Source grid: 3 × 3 × 3 = 27 sources +const AXIAL_MM = [40.0, 55.0, 70.0] +const LATERAL_Y_MM = [-10.0, 0.0, 10.0] +const LATERAL_Z_MM = [-10.0, 0.0, 10.0] + +# Transverse domain: aperture + PML on each side (PML ≈ 4 mm at 0.2 mm grid) +const TRANS_DIM = (APERTURE_MM + 16.0) * 1e-3 # 80 mm + +# Axial domain: skull at 20 mm + deepest source at 70 mm + 30 mm margin +const AXIAL_DIM = 100e-3 # m + +# ── Domain and medium ────────────────────────────────────────────────────────── + +sim_cfg = PAMConfig3D( + dx = DX, + dy = DX, + dz = DX, + axial_dim = AXIAL_DIM, + transverse_dim_y = TRANS_DIM, + transverse_dim_z = TRANS_DIM, + dt = DT, + t_max = T_MAX, + receiver_aperture_y = APERTURE_MM * 1e-3, + receiver_aperture_z = APERTURE_MM * 1e-3, +) + +println("Domain: $(round(Int, AXIAL_DIM*1e3)) mm axial × $(round(Int, TRANS_DIM*1e3)) mm lateral (y & z)") +println("Grid : $(pam_Nx(sim_cfg))×$(pam_Ny(sim_cfg))×$(pam_Nz(sim_cfg)) cells, Nt=$(pam_Nt(sim_cfg))") +println("Aperture: $(round(Int, APERTURE_MM)) mm × $(round(Int, APERTURE_MM)) mm") +println() + +println("Building 3D skull medium (CT slice $SLICE_INDEX, skull at $(round(Int, SKULL_DIST*1e3)) mm)…") +c, rho, med_info = make_pam_medium_3d( + sim_cfg; + aberrator = :skull, + skull_to_transducer = SKULL_DIST, + slice_index_z = SLICE_INDEX, +) +println(" outer skull row : $(med_info[:outer_row])") +println(" inner skull row : $(med_info[:inner_row])") +println(" c₀ (water) : $(sim_cfg.c0) m/s") +println() + +# ── Aperture mask ───────────────────────────────────────────────────────────── + +# The simulation always captures the full ny×nz receiver plane. Restrict to the +# requested aperture by zeroing RF outside the active element range before +# passing to reconstruction, exactly as the 2D validation does. +apt_range_y = receiver_col_range_y(sim_cfg) +apt_range_z = receiver_col_range_z(sim_cfg) +println("Active receiver columns: y=$(apt_range_y), z=$(apt_range_z)") +println() + +# ── Storage ──────────────────────────────────────────────────────────────────── + +n_ax = length(AXIAL_MM) +n_y = length(LATERAL_Y_MM) +n_z = length(LATERAL_Z_MM) + +geo_errors_mm = fill(NaN, n_ax, n_y, n_z) +hasa_errors_mm = fill(NaN, n_ax, n_y, n_z) +geo_recon_ms = fill(NaN, n_ax, n_y, n_z) +hasa_recon_ms = fill(NaN, n_ax, n_y, n_z) +sim_time_s = fill(NaN, n_ax, n_y, n_z) + +# ── Main sweep ──────────────────────────────────────────────────────────────── + +t_sweep_start = time() +n_total = n_ax * n_y * n_z +s_count = 0 + +for (ai, ax_mm) in enumerate(AXIAL_MM), + (yi, ly_mm) in enumerate(LATERAL_Y_MM), + (zi, lz_mm) in enumerate(LATERAL_Z_MM) + + global s_count += 1 + elapsed = time() - t_sweep_start + eta_s = s_count > 1 ? elapsed / (s_count - 1) * (n_total - s_count + 1) : NaN + eta_str = isnan(eta_s) ? "?" : @sprintf("%.0f", eta_s / 60) + @printf("[%2d/%d] ax=%4.0fmm ly=%+5.1fmm lz=%+5.1fmm (ETA ~%s min)\n", + s_count, n_total, ax_mm, ly_mm, lz_mm, eta_str) + + src = PointSource3D( + depth = ax_mm * 1e-3, + lateral_y = ly_mm * 1e-3, + lateral_z = lz_mm * 1e-3, + frequency = FREQ, + num_cycles = NUM_CYCLES, + ) + + # 1. k-Wave simulation (GPU) + t_sim_start = time() + rf_full, kgrid, _ = simulate_point_sources_3d(c, rho, [src], sim_cfg; use_gpu=true) + sim_time_s[ai, yi, zi] = time() - t_sim_start + + # Apply aperture mask: zero RF outside the 64 mm active element window + rf = zeros(eltype(rf_full), size(rf_full)) + rf[apt_range_y, apt_range_z, :] .= rf_full[apt_range_y, apt_range_z, :] + rf_full = nothing # free memory + + # 2. Geometric ASA (corrected=false, GPU) + I_geo, _, geo_info = reconstruct_pam_3d( + rf, c, sim_cfg; + frequencies = [FREQ], + bandwidth = BANDWIDTH, + corrected = false, + axial_step = AXIAL_STEP, + use_gpu = true, + show_progress = false, + ) + geo_recon_ms[ai, yi, zi] = geo_info[:gpu_timing][:march_wall_s] * 1e3 + stats_geo = analyse_pam_3d(I_geo, kgrid, sim_cfg, [src]) + geo_errors_mm[ai, yi, zi] = only(stats_geo[:radial_errors_mm]) + + # 3. HASA (corrected=true, GPU) + I_hasa, _, hasa_info = reconstruct_pam_3d( + rf, c, sim_cfg; + frequencies = [FREQ], + bandwidth = BANDWIDTH, + corrected = true, + axial_step = AXIAL_STEP, + use_gpu = true, + show_progress = false, + ) + hasa_recon_ms[ai, yi, zi] = hasa_info[:gpu_timing][:march_wall_s] * 1e3 + stats_hasa = analyse_pam_3d(I_hasa, kgrid, sim_cfg, [src]) + hasa_errors_mm[ai, yi, zi] = only(stats_hasa[:radial_errors_mm]) + + @printf(" geo=%.2f mm hasa=%.2f mm (geo %.0f ms / hasa %.0f ms GPU march)\n", + geo_errors_mm[ai, yi, zi], hasa_errors_mm[ai, yi, zi], + geo_recon_ms[ai, yi, zi], hasa_recon_ms[ai, yi, zi]) +end + +total_time_min = (time() - t_sweep_start) / 60 +@printf("\nSweep complete in %.1f minutes.\n\n", total_time_min) + +# ── Print summary ───────────────────────────────────────────────────────────── + +println("="^68) +println("3D PAM Localization Error — Fixed $(round(Int, APERTURE_MM)) mm Aperture") +println("="^68) +println() +@printf(" Sources: %d ax × %d y × %d z = %d total\n", n_ax, n_y, n_z, n_total) +@printf(" Frequency: %.1f MHz, Axial step: %.0f µm\n", FREQ/1e6, AXIAL_STEP*1e6) +println() + +geo_all = filter(!isnan, geo_errors_mm) +hasa_all = filter(!isnan, hasa_errors_mm) +@printf(" Geometric ASA : %.2f ± %.2f mm (mean ± std, n=%d)\n", + mean(geo_all), std(geo_all), length(geo_all)) +@printf(" HASA : %.2f ± %.2f mm (mean ± std, n=%d)\n", + mean(hasa_all), std(hasa_all), length(hasa_all)) +println() +println(" Per-depth breakdown:") +println(" Depth │ Geo error mm │ HASA error mm │ Geo ms │ HASA ms") +println(" ──────┼────────────────┼────────────────┼────────┼────────") +for (ai, ax_mm) in enumerate(AXIAL_MM) + gv = filter(!isnan, geo_errors_mm[ai, :, :]) + hv = filter(!isnan, hasa_errors_mm[ai, :, :]) + gm = filter(!isnan, geo_recon_ms[ai, :, :]) + hm = filter(!isnan, hasa_recon_ms[ai, :, :]) + @printf(" %3.0fmm │ %4.2f ± %4.2f mm │ %4.2f ± %4.2f mm │ %6.1f │ %6.1f\n", + ax_mm, mean(gv), std(gv), mean(hv), std(hv), mean(gm), mean(hm)) +end +println() + +# ── Save results ────────────────────────────────────────────────────────────── + +outdir = @__DIR__ +ts = Dates.format(now(), "yyyymmdd_HHMMSS") +outfile = joinpath(outdir, "results_$(ts).jld2") + +jldsave(outfile; + geo_errors_mm, hasa_errors_mm, + geo_recon_ms, hasa_recon_ms, + sim_time_s, + AXIAL_MM, LATERAL_Y_MM, LATERAL_Z_MM, + APERTURE_MM, FREQ, NUM_CYCLES, AXIAL_STEP, + DX, DT, T_MAX, AXIAL_DIM, TRANS_DIM, + SKULL_DIST, SLICE_INDEX, + med_info, + total_time_min, +) +println("Results saved → $outfile") From f9648445e78341266d9cabe6e326f508aeebe4b2 Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 14:34:56 +0200 Subject: [PATCH 03/19] 3d pam accruacy validation (memory issues) --- src/common/kwave_wrapper.jl | 6 +++--- validation/3D_PAM_Accuracy/run_validation.jl | 10 +++++----- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/src/common/kwave_wrapper.jl b/src/common/kwave_wrapper.jl index 484f412..fc39e78 100644 --- a/src/common/kwave_wrapper.jl +++ b/src/common/kwave_wrapper.jl @@ -135,7 +135,7 @@ function _simulate_kwave( ) exec_opts = mods.execopts.SimulationExecutionOptions( is_gpu_simulation=use_gpu, - delete_data=false, + delete_data=true, ) data = mods.kspace.kspaceFirstOrder2D( @@ -238,7 +238,7 @@ function simulate_point_sources( ) exec_opts = mods.execopts.SimulationExecutionOptions( is_gpu_simulation=use_gpu, - delete_data=false, + delete_data=true, ) data = mods.kspace.kspaceFirstOrder2D( @@ -353,7 +353,7 @@ function simulate_point_sources_3d( ) exec_opts = mods.execopts.SimulationExecutionOptions( is_gpu_simulation=use_gpu, - delete_data=false, + delete_data=true, ) data = mods.kspace3d.kspaceFirstOrder3D( diff --git a/validation/3D_PAM_Accuracy/run_validation.jl b/validation/3D_PAM_Accuracy/run_validation.jl index 246546a..0f41be8 100644 --- a/validation/3D_PAM_Accuracy/run_validation.jl +++ b/validation/3D_PAM_Accuracy/run_validation.jl @@ -32,15 +32,15 @@ const SLICE_INDEX = 250 # CT slice (same as 2D validation) const APERTURE_MM = 64.0 # mm — fixed square aperture in y and z # Source grid: 3 × 3 × 3 = 27 sources -const AXIAL_MM = [40.0, 55.0, 70.0] +const AXIAL_MM = [40.0, 50.0, 60.0] const LATERAL_Y_MM = [-10.0, 0.0, 10.0] const LATERAL_Z_MM = [-10.0, 0.0, 10.0] -# Transverse domain: aperture + PML on each side (PML ≈ 4 mm at 0.2 mm grid) -const TRANS_DIM = (APERTURE_MM + 16.0) * 1e-3 # 80 mm +# Transverse domain equals the aperture; k-Wave adds PML outside (pml_inside=false) +const TRANS_DIM = APERTURE_MM * 1e-3 # 64 mm -# Axial domain: skull at 20 mm + deepest source at 70 mm + 30 mm margin -const AXIAL_DIM = 100e-3 # m +# Axial domain: skull at 20 mm + deepest source at 60 mm + 10 mm margin +const AXIAL_DIM = 70e-3 # m # ── Domain and medium ────────────────────────────────────────────────────────── From 181fbf1650f18737c5cc9cbeacf835621dd78af0 Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 15:13:48 +0200 Subject: [PATCH 04/19] delete temp kwave files manually so they dont fill up c during sweep --- src/common/kwave_wrapper.jl | 8 + validation/3D_PAM_Accuracy/run_validation.jl | 33 ++- validation/3D_Scalability/plot_results.jl | 136 +++++++++ validation/3D_Scalability/run_scalability.jl | 276 ++++++++++++++++++ validation/3D_Speed_Benchmark/plot_results.jl | 160 ++++++++++ .../3D_Speed_Benchmark/run_benchmark.jl | 162 ++++++++++ 6 files changed, 764 insertions(+), 11 deletions(-) create mode 100644 validation/3D_Scalability/plot_results.jl create mode 100644 validation/3D_Scalability/run_scalability.jl create mode 100644 validation/3D_Speed_Benchmark/plot_results.jl create mode 100644 validation/3D_Speed_Benchmark/run_benchmark.jl diff --git a/src/common/kwave_wrapper.jl b/src/common/kwave_wrapper.jl index fc39e78..0e9be45 100644 --- a/src/common/kwave_wrapper.jl +++ b/src/common/kwave_wrapper.jl @@ -162,6 +162,7 @@ function simulate_point_sources( sources::AbstractVector{<:EmissionSource2D}, cfg::PAMConfig; use_gpu::Bool=false, + kwave_data_path::Union{Nothing, AbstractString}=nothing, ) isempty(sources) && error("At least one emission source is required.") @@ -230,11 +231,13 @@ function simulate_point_sources( sensor.mask = sensor_mask sensor.record = pc.pybuiltins.list(("p",)) + sim_dir = mktempdir(isnothing(kwave_data_path) ? tempdir() : String(kwave_data_path)) sim_opts = mods.simopts.SimulationOptions( pml_inside=false, pml_size=pml_guard, data_recast=false, save_to_disk=true, + data_path=sim_dir, ) exec_opts = mods.execopts.SimulationExecutionOptions( is_gpu_simulation=use_gpu, @@ -254,6 +257,7 @@ function simulate_point_sources( sensor_data = _as_sensor_matrix(pc.pyconvert(Array, sensor_data_py), length(col_range), nt) rf = zeros(Float64, ny, nt) rf[col_range, :] .= sensor_data + rm(sim_dir; recursive=true, force=true) info = Dict{Symbol, Any}( :receiver_row => row, @@ -271,6 +275,7 @@ function simulate_point_sources_3d( sources::AbstractVector{<:EmissionSource3D}, cfg::PAMConfig3D; use_gpu::Bool=false, + kwave_data_path::Union{Nothing, AbstractString}=nothing, ) isempty(sources) && error("At least one emission source is required.") @@ -345,11 +350,13 @@ function simulate_point_sources_3d( sensor.mask = sensor_mask sensor.record = pc.pybuiltins.list(("p",)) + sim_dir = mktempdir(isnothing(kwave_data_path) ? tempdir() : String(kwave_data_path)) sim_opts = mods.simopts.SimulationOptions( pml_inside=false, pml_size=pml_guard, data_recast=false, save_to_disk=true, + data_path=sim_dir, ) exec_opts = mods.execopts.SimulationExecutionOptions( is_gpu_simulation=use_gpu, @@ -376,6 +383,7 @@ function simulate_point_sources_3d( end # Julia reshape is column-major: ny varies fastest, matching k-Wave's Fortran-order enumeration. rf = reshape(sensor_data_flat, ny, nz, nt) + rm(sim_dir; recursive=true, force=true) info = Dict{Symbol, Any}( :receiver_row => row, diff --git a/validation/3D_PAM_Accuracy/run_validation.jl b/validation/3D_PAM_Accuracy/run_validation.jl index 0f41be8..915a9b8 100644 --- a/validation/3D_PAM_Accuracy/run_validation.jl +++ b/validation/3D_PAM_Accuracy/run_validation.jl @@ -96,6 +96,23 @@ geo_recon_ms = fill(NaN, n_ax, n_y, n_z) hasa_recon_ms = fill(NaN, n_ax, n_y, n_z) sim_time_s = fill(NaN, n_ax, n_y, n_z) +# Progress file: written after every source so a crash loses at most one run. +const PROGRESS_FILE = joinpath(@__DIR__, "progress.jld2") + +function save_progress(;total_elapsed_min=NaN) + jldsave(PROGRESS_FILE; + geo_errors_mm, hasa_errors_mm, + geo_recon_ms, hasa_recon_ms, + sim_time_s, + AXIAL_MM, LATERAL_Y_MM, LATERAL_Z_MM, + APERTURE_MM, FREQ, NUM_CYCLES, AXIAL_STEP, + DX, DT, T_MAX, AXIAL_DIM, TRANS_DIM, + SKULL_DIST, SLICE_INDEX, + med_info, + total_time_min=total_elapsed_min, + ) +end + # ── Main sweep ──────────────────────────────────────────────────────────────── t_sweep_start = time() @@ -162,6 +179,9 @@ for (ai, ax_mm) in enumerate(AXIAL_MM), @printf(" geo=%.2f mm hasa=%.2f mm (geo %.0f ms / hasa %.0f ms GPU march)\n", geo_errors_mm[ai, yi, zi], hasa_errors_mm[ai, yi, zi], geo_recon_ms[ai, yi, zi], hasa_recon_ms[ai, yi, zi]) + + save_progress() + @printf(" [progress saved — %d/%d done]\n", s_count, n_total) end total_time_min = (time() - t_sweep_start) / 60 @@ -203,15 +223,6 @@ outdir = @__DIR__ ts = Dates.format(now(), "yyyymmdd_HHMMSS") outfile = joinpath(outdir, "results_$(ts).jld2") -jldsave(outfile; - geo_errors_mm, hasa_errors_mm, - geo_recon_ms, hasa_recon_ms, - sim_time_s, - AXIAL_MM, LATERAL_Y_MM, LATERAL_Z_MM, - APERTURE_MM, FREQ, NUM_CYCLES, AXIAL_STEP, - DX, DT, T_MAX, AXIAL_DIM, TRANS_DIM, - SKULL_DIST, SLICE_INDEX, - med_info, - total_time_min, -) +save_progress(total_elapsed_min=total_time_min) +mv(PROGRESS_FILE, outfile; force=true) println("Results saved → $outfile") diff --git a/validation/3D_Scalability/plot_results.jl b/validation/3D_Scalability/plot_results.jl new file mode 100644 index 0000000..b41881c --- /dev/null +++ b/validation/3D_Scalability/plot_results.jl @@ -0,0 +1,136 @@ +""" +Plot 3D HASA GPU scalability results. + +Two-panel figure: + (a) Wall-clock time vs aperture — one curve per depth, x-axis annotated + with Ny×Nz voxels per plane (the FFT/memory-bandwidth bottleneck). + (b) Wall-clock time vs reconstruction depth — one curve per aperture, + showing the linear growth from increased marching-step count. + +Usage: + julia --project=. validation/3D_Scalability/plot_results.jl [results_file.jld2] +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using CairoMakie, JLD2, Printf + +# ── Load ────────────────────────────────────────────────────────────────────── + +results_dir = @__DIR__ +results_file = if !isempty(ARGS) + ARGS[1] +else + files = filter(f -> startswith(f, "results_") && endswith(f, ".jld2"), readdir(results_dir)) + isempty(files) && error("No results_*.jld2 in $results_dir. Run run_scalability.jl first.") + joinpath(results_dir, last(sort(files))) +end +println("Loading: $results_file") + +d = load(results_file) +timing_wall_s = d["timing_wall_s"] # (n_depths × n_apertures) +APERTURES_MM = d["APERTURES_MM"] +DEPTHS_MM = d["DEPTHS_MM"] +DX = d["DX"] +AXIAL_STEP = d["AXIAL_STEP"] + +n_depths = length(DEPTHS_MM) +n_apertures = length(APERTURES_MM) + +# ── Derived labels ───────────────────────────────────────────────────────────── + +Ny_vals = round.(Int, APERTURES_MM .* 1e-3 ./ DX) +vox_k = round.(Int, Ny_vals .^ 2 ./ 1000) +march_steps = round.(Int, DEPTHS_MM .* 1e-3 ./ AXIAL_STEP) + +# Tick labels for aperture axis: "50 mm\n(250×250=62k)" +apt_tick_labels = [@sprintf("%d mm\n(%d×%d=%dk)", round(Int,a), n, n, v) + for (a, n, v) in zip(APERTURES_MM, Ny_vals, vox_k)] + +# Print summary table +println() +println("Wall-clock GPU HASA [s] (rows = depth from skull, cols = aperture)") +@printf(" %12s │", "Depth \\ Apt") +for apt_mm in APERTURES_MM + @printf(" %5.0f mm", apt_mm) +end +println() +for (di, depth_mm) in enumerate(DEPTHS_MM) + @printf(" %8.0f mm │", depth_mm) + for ai in 1:n_apertures + @printf(" %6.2f s", timing_wall_s[di, ai]) + end + println() +end +println() + +# ── Figure ──────────────────────────────────────────────────────────────────── + +update_theme!(fontsize = 9) + +DEPTH_COLORS = [:steelblue, :coral, :forestgreen, :darkorchid, :darkorange] +APT_MARKERS = [:circle, :diamond, :rect] + +fig = Figure(size = (820, 370)) + +# ── (a) Time vs aperture (one curve per depth) ───────────────────────────────── + +ax_l = Axis(fig[1, 1]; + title = "(a) Scaling with transverse grid size", + xlabel = "Aperture [mm] (Ny × Nz voxels/plane)", + ylabel = "GPU HASA wall-clock [s]", + xticks = (APERTURES_MM, apt_tick_labels), + xticklabelsize = 8, +) + +for (di, depth_mm) in enumerate(DEPTHS_MM) + label = @sprintf("%d mm depth", round(Int, depth_mm)) + lines!(ax_l, APERTURES_MM, timing_wall_s[di, :]; + label = label, + color = DEPTH_COLORS[di], + linewidth = 1.5, + ) + scatter!(ax_l, APERTURES_MM, timing_wall_s[di, :]; + color = DEPTH_COLORS[di], + markersize = 7, + ) +end + +axislegend(ax_l; title = "Recon depth\n(below skull)", position = :lt, + labelsize = 8, titlesize = 8) + +# ── (b) Time vs depth (one curve per aperture) ───────────────────────────────── + +ax_r = Axis(fig[1, 2]; + title = "(b) Scaling with reconstruction depth", + xlabel = "Reconstruction depth below skull [mm]", + ylabel = "GPU HASA wall-clock [s]", + xticks = (DEPTHS_MM, string.(round.(Int, DEPTHS_MM))), +) + +for (ai, apt_mm) in enumerate(APERTURES_MM) + Ny = Ny_vals[ai] + label = @sprintf("%d mm (%d×%d = %dk vox)", round(Int,apt_mm), Ny, Ny, vox_k[ai]) + lines!(ax_r, DEPTHS_MM, timing_wall_s[:, ai]; + label = label, + color = DEPTH_COLORS[ai], + linewidth = 1.5, + ) + scatter!(ax_r, DEPTHS_MM, timing_wall_s[:, ai]; + color = DEPTH_COLORS[ai], + marker = APT_MARKERS[ai], + markersize = 7, + ) +end + +axislegend(ax_r; title = "Aperture\n(voxels/plane)", position = :lt, + labelsize = 8, titlesize = 8) + +colgap!(fig.layout, 22) + +# ── Save ────────────────────────────────────────────────────────────────────── + +figfile = replace(results_file, r"\.jld2$" => "_scalability.pdf") +save(figfile, fig) +println("Saved → $figfile") diff --git a/validation/3D_Scalability/run_scalability.jl b/validation/3D_Scalability/run_scalability.jl new file mode 100644 index 0000000..a6878d5 --- /dev/null +++ b/validation/3D_Scalability/run_scalability.jl @@ -0,0 +1,276 @@ +""" +3D HASA GPU Scalability Study — reconstruction time vs aperture and depth. + +One k-Wave simulation (64 mm aperture, source at 50 mm — same parameters as +the speed benchmark) provides the base RF data. The reconstruction config is +then swept over all (depth, aperture) combinations to isolate the two +independent GPU compute bottlenecks: + + Transverse grid size Ny×Nz → FFT / memory-bandwidth bottleneck + Axial reconstruction depth → marching-step count, scales linearly + +Aperture sweep uses crop / zero-pad of the base RF data so that no additional +k-Wave simulations are required; only GPU HASA reconstruction is timed. + +Inner-loop structure for a single call (nfreq=1, nwindows=1): + n_march_rows = depth_mm / (AXIAL_STEP*1e3) (linear in depth) + ops per row = 4 substeps (HASA) × 2D FFT on Ny×Nz + +Run from the project root: + julia --project=. validation/3D_Scalability/run_scalability.jl +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using TranscranialFUS +using JLD2, Printf, Dates + +# ── Fixed parameters (consistent with 3D_PAM_Accuracy / 3D_Speed_Benchmark) ── + +const FREQ = 1.0e6 +const NUM_CYCLES = 10.0 +const DX = 0.2e-3 +const DT = 40e-9 +const T_MAX = 120e-6 +const AXIAL_STEP = 50e-6 +const BANDWIDTH = 0.0 + +const SKULL_DIST = 20e-3 +const SLICE_INDEX = 250 + +# ── Sweep parameters ────────────────────────────────────────────────────────── + +const APERTURES_MM = [50.0, 75.0, 100.0] # receiver aperture (y and z) +const DEPTHS_MM = [20.0, 40.0, 60.0, 80.0, 100.0] # depth below skull surface + +let apts = round.(Int, APERTURES_MM .* 1e-3 ./ DX) + println("Aperture sweep: $(round.(Int, APERTURES_MM)) mm → Ny=Nz = $apts") + println(" voxels/plane : $(apts .^ 2)") +end +let steps = round.(Int, DEPTHS_MM .* 1e-3 ./ AXIAL_STEP) + println("Depth sweep : $(round.(Int, DEPTHS_MM)) mm below skull") + println(" march steps : $steps (×4 substeps for HASA)") +end +println() + +# ── k-Wave simulation (64 mm aperture — same as speed benchmark) ────────────── + +const KW_APERTURE = 64e-3 +const KW_AXIAL_DIM = 70e-3 + +kw_cfg = PAMConfig3D( + dx = DX, + dy = DX, + dz = DX, + axial_dim = KW_AXIAL_DIM, + transverse_dim_y = KW_APERTURE, + transverse_dim_z = KW_APERTURE, + dt = DT, + t_max = T_MAX, + receiver_aperture_y = KW_APERTURE, + receiver_aperture_z = KW_APERTURE, +) + +println("k-Wave grid : $(pam_Nx(kw_cfg))×$(pam_Ny(kw_cfg))×$(pam_Nz(kw_cfg)), Nt=$(pam_Nt(kw_cfg))") +println() + +println("Building skull medium for k-Wave…") +c_kw, rho_kw, _ = make_pam_medium_3d( + kw_cfg; + aberrator = :skull, + skull_to_transducer = SKULL_DIST, + slice_index_z = SLICE_INDEX, +) + +src = PointSource3D( + depth = 50e-3, + lateral_y = 0.0, + lateral_z = 0.0, + frequency = FREQ, + num_cycles = NUM_CYCLES, +) + +println("Running k-Wave (GPU)…") +t_sim = @elapsed begin + rf_base, _, _ = simulate_point_sources_3d(c_kw, rho_kw, [src], kw_cfg; use_gpu=true) +end +@printf(" k-Wave wall-clock: %.1f s\n\n", t_sim) + +const Ny_base = pam_Ny(kw_cfg) # 320 (64 mm / 0.2 mm) +const Nz_base = pam_Nz(kw_cfg) # 320 + +# ── RF resize helper (centre crop or zero-pad) ──────────────────────────────── + +function resize_rf(rf::AbstractArray, Ny_target::Int, Nz_target::Int) + Ny_src, Nz_src, Nt = size(rf) + rf_out = zeros(eltype(rf), Ny_target, Nz_target, Nt) + + if Ny_target <= Ny_src + y_src_lo = (Ny_src - Ny_target) ÷ 2 + 1 + y_range_src = y_src_lo:(y_src_lo + Ny_target - 1) + y_range_dst = 1:Ny_target + else + y_dst_lo = (Ny_target - Ny_src) ÷ 2 + 1 + y_range_src = 1:Ny_src + y_range_dst = y_dst_lo:(y_dst_lo + Ny_src - 1) + end + + if Nz_target <= Nz_src + z_src_lo = (Nz_src - Nz_target) ÷ 2 + 1 + z_range_src = z_src_lo:(z_src_lo + Nz_target - 1) + z_range_dst = 1:Nz_target + else + z_dst_lo = (Nz_target - Nz_src) ÷ 2 + 1 + z_range_src = 1:Nz_src + z_range_dst = z_dst_lo:(z_dst_lo + Nz_src - 1) + end + + rf_out[y_range_dst, z_range_dst, :] .= rf[y_range_src, z_range_src, :] + return rf_out +end + +# ── GPU warm-up ─────────────────────────────────────────────────────────────── + +print("GPU warm-up (small domain) … ") +flush(stdout) +let + cfg_w = PAMConfig3D( + dx = DX, dy = DX, dz = DX, + axial_dim = 30e-3, + transverse_dim_y = 50e-3, + transverse_dim_z = 50e-3, + dt = DT, t_max = T_MAX, + receiver_aperture_y = 50e-3, + receiver_aperture_z = 50e-3, + ) + c_w, _, _ = make_pam_medium_3d(cfg_w; + aberrator=:skull, skull_to_transducer=SKULL_DIST, slice_index_z=SLICE_INDEX) + rf_w = zeros(Float32, pam_Ny(cfg_w), pam_Nz(cfg_w), pam_Nt(cfg_w)) + reconstruct_pam_3d(rf_w, c_w, cfg_w; + frequencies=[FREQ], bandwidth=BANDWIDTH, corrected=true, + axial_step=AXIAL_STEP, use_gpu=true, show_progress=false) +end +println("done.\n") + +# ── Scalability sweep ───────────────────────────────────────────────────────── + +n_depths = length(DEPTHS_MM) +n_apertures = length(APERTURES_MM) + +timing_wall_s = fill(NaN, n_depths, n_apertures) +timing_march_s = fill(NaN, n_depths, n_apertures) + +t_sweep_start = time() +n_total = n_depths * n_apertures +s_count = 0 + +for (di, depth_mm) in enumerate(DEPTHS_MM) + + recon_axial_dim = (depth_mm + SKULL_DIST * 1e3) * 1e-3 # skull + depth in metres + + # Build medium for max aperture at this depth; crop for smaller apertures. + cfg_max = PAMConfig3D( + dx = DX, + dy = DX, + dz = DX, + axial_dim = recon_axial_dim, + transverse_dim_y = maximum(APERTURES_MM) * 1e-3, + transverse_dim_z = maximum(APERTURES_MM) * 1e-3, + dt = DT, + t_max = T_MAX, + receiver_aperture_y = maximum(APERTURES_MM) * 1e-3, + receiver_aperture_z = maximum(APERTURES_MM) * 1e-3, + ) + c_max, _, _ = make_pam_medium_3d(cfg_max; + aberrator=:skull, skull_to_transducer=SKULL_DIST, slice_index_z=SLICE_INDEX) + Ny_max = pam_Ny(cfg_max) # 500 + + for (ai, apt_mm) in enumerate(APERTURES_MM) + + global s_count += 1 + Ny_tgt = round(Int, apt_mm * 1e-3 / DX) + @printf("[%2d/%d] depth=%3.0f mm, aperture=%3.0f mm (Ny=Nz=%d, %d march rows) … ", + s_count, n_total, depth_mm, apt_mm, Ny_tgt, + round(Int, depth_mm * 1e-3 / AXIAL_STEP)) + flush(stdout) + + # Reconstruction config for this (depth, aperture) + cfg_recon = PAMConfig3D( + dx = DX, + dy = DX, + dz = DX, + axial_dim = recon_axial_dim, + transverse_dim_y = apt_mm * 1e-3, + transverse_dim_z = apt_mm * 1e-3, + dt = DT, + t_max = T_MAX, + receiver_aperture_y = apt_mm * 1e-3, + receiver_aperture_z = apt_mm * 1e-3, + ) + + # Crop medium from the max-aperture build (centre slice) + y_lo = (Ny_max - Ny_tgt) ÷ 2 + 1 + y_hi = y_lo + Ny_tgt - 1 + c_recon = c_max[:, y_lo:y_hi, y_lo:y_hi] + + # RF resized to match aperture (crop or zero-pad from 64 mm base) + rf_apt = resize_rf(rf_base, Ny_tgt, Ny_tgt) + + # GPU HASA reconstruction + t_wall = @elapsed begin + _, _, info = reconstruct_pam_3d( + rf_apt, c_recon, cfg_recon; + frequencies = [FREQ], + bandwidth = BANDWIDTH, + corrected = true, + axial_step = AXIAL_STEP, + use_gpu = true, + show_progress = false, + ) + timing_march_s[di, ai] = get(get(info, :gpu_timing, Dict()), :march_wall_s, NaN) + end + + timing_wall_s[di, ai] = t_wall + + @printf("%.2f s (march %.2f s)\n", t_wall, timing_march_s[di, ai]) + end +end + +total_min = (time() - t_sweep_start) / 60 +@printf("\nSweep complete in %.1f minutes.\n\n", total_min) + +# ── Summary table ───────────────────────────────────────────────────────────── + +println("Wall-clock GPU HASA [s] (rows = depth from skull, cols = aperture)") +@printf(" %10s │", "Depth \\ Apt") +for apt_mm in APERTURES_MM + @printf(" %5.0f mm", apt_mm) +end +println() +println(" " * "─"^11 * "┼" * "─"^(9 * n_apertures)) +for (di, depth_mm) in enumerate(DEPTHS_MM) + @printf(" %6.0f mm │", depth_mm) + for (ai, _) in enumerate(APERTURES_MM) + @printf(" %7.2f s", timing_wall_s[di, ai]) + end + println() +end +println() + +# ── Save ────────────────────────────────────────────────────────────────────── + +outdir = @__DIR__ +ts = Dates.format(now(), "yyyymmdd_HHMMSS") +outfile = joinpath(outdir, "results_$(ts).jld2") + +jldsave(outfile; + timing_wall_s, + timing_march_s, + APERTURES_MM, + DEPTHS_MM, + FREQ, NUM_CYCLES, DX, DT, T_MAX, AXIAL_STEP, BANDWIDTH, + SKULL_DIST, SLICE_INDEX, + sim_time_s = t_sim, +) +println("Results saved → $outfile") diff --git a/validation/3D_Speed_Benchmark/plot_results.jl b/validation/3D_Speed_Benchmark/plot_results.jl new file mode 100644 index 0000000..642781a --- /dev/null +++ b/validation/3D_Speed_Benchmark/plot_results.jl @@ -0,0 +1,160 @@ +""" +Plot 3D PAM speed benchmark results. + +Produces a figure with: + - 2×2 grid: Y-Z cross-section at source depth for each mode + (CPU ASA | GPU ASA) / (CPU HASA | GPU HASA) + - Bar chart: wall-clock reconstruction time per mode (log scale) + +Usage: + julia --project=. validation/3D_Speed_Benchmark/plot_results.jl [results_file.jld2] +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using CairoMakie, JLD2, TranscranialFUS, Printf + +# ── Load ────────────────────────────────────────────────────────────────────── + +results_dir = @__DIR__ +results_file = if !isempty(ARGS) + ARGS[1] +else + files = filter(f -> startswith(f, "results_") && endswith(f, ".jld2"), readdir(results_dir)) + isempty(files) && error("No results_*.jld2 in $results_dir. Run run_benchmark.jl first.") + joinpath(results_dir, last(sort(files))) +end +println("Loading: $results_file") + +d = load(results_file) +intensities = d["intensities"] +wall_times = d["wall_times"] +DX = d["DX"] +DT = d["DT"] +T_MAX = d["T_MAX"] +APERTURE = d["APERTURE"] +AXIAL_DIM = d["AXIAL_DIM"] +TRANS_DIM = d["TRANS_DIM"] +SKULL_DIST = d["SKULL_DIST"] +SLICE_INDEX = d["SLICE_INDEX"] +FREQ = d["FREQ"] +NUM_CYCLES = d["NUM_CYCLES"] + +# ── Rebuild config for coordinate arrays ────────────────────────────────────── + +sim_cfg = PAMConfig3D( + dx = DX, + dy = DX, + dz = DX, + axial_dim = AXIAL_DIM, + transverse_dim_y = TRANS_DIM, + transverse_dim_z = TRANS_DIM, + dt = DT, + t_max = T_MAX, + receiver_aperture_y = APERTURE, + receiver_aperture_z = APERTURE, +) + +rr = receiver_row(sim_cfg) +Ny = pam_Ny(sim_cfg) +Nz = pam_Nz(sim_cfg) +dx_mm = DX * 1e3 + +y_coords = [(j - (Ny ÷ 2 + 1)) * dx_mm for j in 1:Ny] +z_coords = [(k - (Nz ÷ 2 + 1)) * dx_mm for k in 1:Nz] + +# Source is at 50 mm depth from receiver +src_row = rr + round(Int, 50e-3 / DX) +src_row = clamp(src_row, 1, pam_Nx(sim_cfg)) + +# ── Print summary ───────────────────────────────────────────────────────────── + +LABELS = ["CPU_ASA", "GPU_ASA", "CPU_HASA", "GPU_HASA"] + +println() +println(" Mode │ Wall-clock") +println(" ───────────┼───────────") +for lbl in LABELS + @printf(" %-10s │ %7.2f s\n", lbl, wall_times[lbl]) +end +println() + +# ── Figure ──────────────────────────────────────────────────────────────────── + +update_theme!(fontsize = 9) + +fig = Figure(size = (900, 720)) + +PANEL_LABELS = ["CPU — Geometric ASA", "GPU — Geometric ASA", + "CPU — HASA", "GPU — HASA"] +PANEL_KEYS = ["CPU_ASA", "GPU_ASA", "CPU_HASA", "GPU_HASA"] +POSITIONS = [(1, 1), (1, 2), (2, 1), (2, 2)] + +for (lbl, title, pos) in zip(PANEL_KEYS, PANEL_LABELS, POSITIONS) + I = intensities[lbl] + slice = I[src_row, :, :] # (Ny, Nz) — Y-Z plane at source depth + I_max = max(maximum(slice), 1f-30) + slice_db = 20f0 .* log10.(slice ./ I_max .+ 1f-10) + + ax = Axis(fig[pos[1], pos[2]]; + title = @sprintf("%s\n%.2f s", title, wall_times[lbl]), + xlabel = "Lateral Z [mm]", + ylabel = "Lateral Y [mm]", + aspect = DataAspect(), + ) + heatmap!(ax, z_coords, y_coords, slice_db'; + colorrange = (-40, 0), + colormap = :inferno, + ) +end + +# Shared colorbar +Colorbar(fig[1:2, 3]; + colorrange = (-40, 0), + colormap = :inferno, + label = "Normalised intensity [dB]", + width = 14, + ticklabelsize = 8, + labelsize = 9, + ticks = -40:10:0, +) + +# Timing bar chart +ax_bar = Axis(fig[3, 1:2]; + title = "Reconstruction wall-clock time", + ylabel = "Time [s]", + yscale = log10, + xticks = (1:4, LABELS), + xticklabelsize = 9, +) + +bar_vals = [wall_times[l] for l in LABELS] +bar_colors = [:steelblue, :coral, :steelblue, :coral] +barplot!(ax_bar, 1:4, bar_vals; color = bar_colors, strokewidth = 0.5, strokecolor = :black) + +# Annotate each bar with its value +for (i, v) in enumerate(bar_vals) + text!(ax_bar, i, v * 1.3; + text = @sprintf("%.1f s", v), + align = (:center, :bottom), + fontsize = 8, + ) +end + +Legend(fig[3, 3], + [PolyElement(color=:steelblue), PolyElement(color=:coral)], + ["ASA", "HASA"]; + framevisible = false, + labelsize = 9, +) + +rowgap!(fig.layout, 10) +colgap!(fig.layout, 8) +rowsize!(fig.layout, 3, Relative(0.28)) + +# ── Save ────────────────────────────────────────────────────────────────────── + +figfile = replace(results_file, r"\.jld2$" => "_speed_benchmark.pdf") +save(figfile, fig) +println("Saved → $figfile") diff --git a/validation/3D_Speed_Benchmark/run_benchmark.jl b/validation/3D_Speed_Benchmark/run_benchmark.jl new file mode 100644 index 0000000..8067e2b --- /dev/null +++ b/validation/3D_Speed_Benchmark/run_benchmark.jl @@ -0,0 +1,162 @@ +""" +3D HASA Speed Benchmark — CPU vs GPU, ASA vs HASA. + +A single centre source (50 mm depth, lateral = 0) is simulated once with +k-Wave (GPU). The RF data is then reconstructed with all four mode +combinations and wall-clock times are recorded for direct comparison: + CPU ASA | CPU HASA + GPU ASA | GPU HASA + +Parameters match validation/3D_PAM_Accuracy/run_validation.jl exactly. + +Run from the project root: + julia --project=. validation/3D_Speed_Benchmark/run_benchmark.jl +""" + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..", "..")) + +using TranscranialFUS +using JLD2, Printf, Dates + +# ── Configuration (identical to 3D_PAM_Accuracy) ────────────────────────────── + +const FREQ = 1.0e6 +const NUM_CYCLES = 10.0 +const DX = 0.2e-3 +const DT = 40e-9 +const T_MAX = 120e-6 +const AXIAL_STEP = 50e-6 +const BANDWIDTH = 0.0 + +const SKULL_DIST = 20e-3 +const SLICE_INDEX = 250 +const APERTURE = 64e-3 + +const AXIAL_DIM = 70e-3 +const TRANS_DIM = APERTURE + +# ── Domain and medium ───────────────────────────────────────────────────────── + +sim_cfg = PAMConfig3D( + dx = DX, + dy = DX, + dz = DX, + axial_dim = AXIAL_DIM, + transverse_dim_y = TRANS_DIM, + transverse_dim_z = TRANS_DIM, + dt = DT, + t_max = T_MAX, + receiver_aperture_y = APERTURE, + receiver_aperture_z = APERTURE, +) + +println("Domain : $(round(Int, AXIAL_DIM*1e3)) mm axial × $(round(Int, TRANS_DIM*1e3)) mm transverse") +println("Grid : $(pam_Nx(sim_cfg))×$(pam_Ny(sim_cfg))×$(pam_Nz(sim_cfg)) cells, Nt=$(pam_Nt(sim_cfg))") +println("Aperture: $(round(Int, APERTURE*1e3)) mm × $(round(Int, APERTURE*1e3)) mm") +println() + +println("Building skull medium (CT slice $SLICE_INDEX, skull at $(round(Int, SKULL_DIST*1e3)) mm)…") +c, rho, med_info = make_pam_medium_3d( + sim_cfg; + aberrator = :skull, + skull_to_transducer = SKULL_DIST, + slice_index_z = SLICE_INDEX, +) +println(" outer skull row : $(med_info[:outer_row])") +println(" inner skull row : $(med_info[:inner_row])") +println() + +# ── Single centre source ─────────────────────────────────────────────────────── + +src = PointSource3D( + depth = 50e-3, + lateral_y = 0.0, + lateral_z = 0.0, + frequency = FREQ, + num_cycles = NUM_CYCLES, +) + +# ── k-Wave simulation ───────────────────────────────────────────────────────── + +println("Running k-Wave (GPU)…") +t_sim = @elapsed begin + rf_full, kgrid, _ = simulate_point_sources_3d(c, rho, [src], sim_cfg; use_gpu=true) +end +@printf(" k-Wave wall-clock : %.1f s\n\n", t_sim) + +apt_range_y = receiver_col_range_y(sim_cfg) +apt_range_z = receiver_col_range_z(sim_cfg) +rf = zeros(eltype(rf_full), size(rf_full)) +rf[apt_range_y, apt_range_z, :] .= rf_full[apt_range_y, apt_range_z, :] +rf_full = nothing + +# ── Four reconstructions ────────────────────────────────────────────────────── + +const MODES = [ + (use_gpu=false, corrected=false, label="CPU_ASA"), + (use_gpu=false, corrected=true, label="CPU_HASA"), + (use_gpu=true, corrected=false, label="GPU_ASA"), + (use_gpu=true, corrected=true, label="GPU_HASA"), +] + +intensities = Dict{String,Array{Float32,3}}() +info_dicts = Dict{String,Any}() +wall_times = Dict{String,Float64}() + +println("Reconstructions:") +for m in MODES + @printf(" %-10s … ", m.label) + flush(stdout) + t = @elapsed begin + I, _, info = reconstruct_pam_3d( + rf, c, sim_cfg; + frequencies = [FREQ], + bandwidth = BANDWIDTH, + corrected = m.corrected, + axial_step = AXIAL_STEP, + use_gpu = m.use_gpu, + show_progress = false, + ) + intensities[m.label] = I + info_dicts[m.label] = info + end + wall_times[m.label] = t + @printf("%.2f s\n", t) +end + +# ── Summary ─────────────────────────────────────────────────────────────────── + +println() +println("="^52) +println("3D PAM Speed Benchmark — $(round(Int, APERTURE*1e3)) mm aperture, source at 50 mm") +println("="^52) +println() +println(" Mode │ Wall-clock") +println(" ───────────┼───────────") +for m in MODES + @printf(" %-10s │ %7.2f s\n", m.label, wall_times[m.label]) +end +println() +@printf(" GPU/CPU speedup (HASA): %.1f×\n", + wall_times["CPU_HASA"] / wall_times["GPU_HASA"]) +@printf(" GPU/CPU speedup (ASA) : %.1f×\n", + wall_times["CPU_ASA"] / wall_times["GPU_ASA"]) +println() + +# ── Save ────────────────────────────────────────────────────────────────────── + +outdir = @__DIR__ +ts = Dates.format(now(), "yyyymmdd_HHMMSS") +outfile = joinpath(outdir, "results_$(ts).jld2") + +jldsave(outfile; + intensities, + wall_times, + info_dicts, + sim_time_s = t_sim, + FREQ, NUM_CYCLES, DX, DT, T_MAX, AXIAL_STEP, BANDWIDTH, + AXIAL_DIM, TRANS_DIM, APERTURE, SKULL_DIST, SLICE_INDEX, + med_info, +) +println("Results saved → $outfile") From 3709b27ff3f227af5a1114705d41bc872b3196d6 Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 15:16:25 +0200 Subject: [PATCH 05/19] resume logic for 3d accuracy sweep --- validation/3D_PAM_Accuracy/run_validation.jl | 30 ++++++++++++++++++-- 1 file changed, 27 insertions(+), 3 deletions(-) diff --git a/validation/3D_PAM_Accuracy/run_validation.jl b/validation/3D_PAM_Accuracy/run_validation.jl index 915a9b8..43bc486 100644 --- a/validation/3D_PAM_Accuracy/run_validation.jl +++ b/validation/3D_PAM_Accuracy/run_validation.jl @@ -99,6 +99,19 @@ sim_time_s = fill(NaN, n_ax, n_y, n_z) # Progress file: written after every source so a crash loses at most one run. const PROGRESS_FILE = joinpath(@__DIR__, "progress.jld2") +# Resume from a previous partial run if the progress file exists. +if isfile(PROGRESS_FILE) + prev = load(PROGRESS_FILE) + geo_errors_mm .= prev["geo_errors_mm"] + hasa_errors_mm .= prev["hasa_errors_mm"] + geo_recon_ms .= prev["geo_recon_ms"] + hasa_recon_ms .= prev["hasa_recon_ms"] + sim_time_s .= prev["sim_time_s"] + n_done = count(!isnan, geo_errors_mm) + println("Resuming from progress.jld2 — $n_done/$(n_ax*n_y*n_z) sources already done.") + println() +end + function save_progress(;total_elapsed_min=NaN) jldsave(PROGRESS_FILE; geo_errors_mm, hasa_errors_mm, @@ -117,15 +130,24 @@ end t_sweep_start = time() n_total = n_ax * n_y * n_z -s_count = 0 +s_count = 0 # index across all sources (including already-done ones) +n_run = 0 # sources actually simulated this session (for ETA) for (ai, ax_mm) in enumerate(AXIAL_MM), (yi, ly_mm) in enumerate(LATERAL_Y_MM), (zi, lz_mm) in enumerate(LATERAL_Z_MM) global s_count += 1 + + if !isnan(geo_errors_mm[ai, yi, zi]) + @printf("[%2d/%d] ax=%4.0fmm ly=%+5.1fmm lz=%+5.1fmm [skipped — already done]\n", + s_count, n_total, ax_mm, ly_mm, lz_mm) + continue + end + + n_remaining = count(isnan, geo_errors_mm) elapsed = time() - t_sweep_start - eta_s = s_count > 1 ? elapsed / (s_count - 1) * (n_total - s_count + 1) : NaN + eta_s = n_run > 0 ? elapsed / n_run * (n_remaining - 1) : NaN eta_str = isnan(eta_s) ? "?" : @sprintf("%.0f", eta_s / 60) @printf("[%2d/%d] ax=%4.0fmm ly=%+5.1fmm lz=%+5.1fmm (ETA ~%s min)\n", s_count, n_total, ax_mm, ly_mm, lz_mm, eta_str) @@ -180,8 +202,10 @@ for (ai, ax_mm) in enumerate(AXIAL_MM), geo_errors_mm[ai, yi, zi], hasa_errors_mm[ai, yi, zi], geo_recon_ms[ai, yi, zi], hasa_recon_ms[ai, yi, zi]) + global n_run += 1 + n_done = n_total - count(isnan, geo_errors_mm) save_progress() - @printf(" [progress saved — %d/%d done]\n", s_count, n_total) + @printf(" [progress saved — %d/%d done]\n", n_done, n_total) end total_time_min = (time() - t_sweep_start) / 60 From e54c287a5d54cd68639e7f1d002ae00cd302b939 Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 16:30:06 +0200 Subject: [PATCH 06/19] visualisation pipeline --- src/common/kwave_wrapper.jl | 73 ++- visualisation/README.md | 81 +++ visualisation/make_window_convergence.jl | 720 +++++++++++++++++++++++ 3 files changed, 849 insertions(+), 25 deletions(-) create mode 100644 visualisation/README.md create mode 100644 visualisation/make_window_convergence.jl diff --git a/src/common/kwave_wrapper.jl b/src/common/kwave_wrapper.jl index 0e9be45..c25efd2 100644 --- a/src/common/kwave_wrapper.jl +++ b/src/common/kwave_wrapper.jl @@ -244,20 +244,31 @@ function simulate_point_sources( delete_data=true, ) - data = mods.kspace.kspaceFirstOrder2D( - kgrid=deepcopy_py(py_kgrid), - medium=deepcopy_py(medium), - source=deepcopy_py(source), - sensor=deepcopy_py(sensor), - simulation_options=sim_opts, - execution_options=exec_opts, - ) - - sensor_data_py = np.array(data["p"], dtype=np.float64) - sensor_data = _as_sensor_matrix(pc.pyconvert(Array, sensor_data_py), length(col_range), nt) + sensor_data = let + data = mods.kspace.kspaceFirstOrder2D( + kgrid=deepcopy_py(py_kgrid), + medium=deepcopy_py(medium), + source=deepcopy_py(source), + sensor=deepcopy_py(sensor), + simulation_options=sim_opts, + execution_options=exec_opts, + ) + raw = pc.pyconvert(Array, np.array(data["p"], dtype=np.float64)) + _as_sensor_matrix(raw, length(col_range), nt) + # data and intermediate Python objects go out of scope here + end rf = zeros(Float64, ny, nt) rf[col_range, :] .= sensor_data - rm(sim_dir; recursive=true, force=true) + # Retry rm: Python's refcounting closes h5py handles as the let-scoped + # Py objects are finalized by Julia's natural GC between retries. + for attempt in 1:10 + try + rm(sim_dir; recursive=true, force=true) + break + catch + attempt < 10 && sleep(0.5) + end + end info = Dict{Symbol, Any}( :receiver_row => row, @@ -363,18 +374,21 @@ function simulate_point_sources_3d( delete_data=true, ) - data = mods.kspace3d.kspaceFirstOrder3D( - kgrid=deepcopy_py(py_kgrid), - medium=deepcopy_py(medium), - source=deepcopy_py(source), - sensor=deepcopy_py(sensor), - simulation_options=sim_opts, - execution_options=exec_opts, - ) - - sensor_data_py = np.array(data["p"], dtype=np.float64) - # k-Wave returns (Nt, ny*nz) in Python (row-major). pyconvert gives (ny*nz, Nt) in Julia. - sensor_data_flat = pc.pyconvert(Matrix{Float64}, sensor_data_py) # (ny*nz, Nt) or (Nt, ny*nz) + # Wrap in let so data/sensor_data_py go out of scope before GC, releasing h5py handles. + sensor_data_flat = let + data = mods.kspace3d.kspaceFirstOrder3D( + kgrid=deepcopy_py(py_kgrid), + medium=deepcopy_py(medium), + source=deepcopy_py(source), + sensor=deepcopy_py(sensor), + simulation_options=sim_opts, + execution_options=exec_opts, + ) + # k-Wave returns (Nt, ny*nz) in Python (row-major). pyconvert gives (ny*nz, Nt) in Julia. + flat = pc.pyconvert(Matrix{Float64}, np.array(data["p"], dtype=np.float64)) + # data and intermediate Python objects go out of scope here + flat + end # Normalise to (ny*nz, Nt) regardless of which axis k-Wave put time on. if size(sensor_data_flat, 1) == nt && size(sensor_data_flat, 2) == ny * nz sensor_data_flat = permutedims(sensor_data_flat) # → (ny*nz, Nt) @@ -383,7 +397,16 @@ function simulate_point_sources_3d( end # Julia reshape is column-major: ny varies fastest, matching k-Wave's Fortran-order enumeration. rf = reshape(sensor_data_flat, ny, nz, nt) - rm(sim_dir; recursive=true, force=true) + # Retry rm: Python's refcounting closes h5py handles as the let-scoped + # Py objects are finalized by Julia's natural GC between retries. + for attempt in 1:10 + try + rm(sim_dir; recursive=true, force=true) + break + catch + attempt < 10 && sleep(0.5) + end + end info = Dict{Symbol, Any}( :receiver_row => row, diff --git a/visualisation/README.md b/visualisation/README.md new file mode 100644 index 0000000..7595d0c --- /dev/null +++ b/visualisation/README.md @@ -0,0 +1,81 @@ +# PAM Window Convergence Visualisation + +This folder contains a self-contained 3D PAM animation pipeline. It generates a +synthetic vascular-network source distribution, simulates RF data, reconstructs +the case window by window with HASA, chooses the final source-F1-optimal +threshold, and renders a fixed-threshold convergence movie. + +## Run + +```powershell +julia --project=. visualisation/make_window_convergence.jl +``` + +Default case: + +- 3D network source at `45:0:0 mm` +- CT skull aberrator, `slice-index=250`, skull distance `20 mm` +- `dx=0.2 mm`, `dy=0.2 mm`, `dz=0.2 mm` +- `t_max=400 us` +- `40 us` windows, `20 us` hop +- `40 kHz` reconstruction bandwidth +- GPU k-Wave and GPU reconstruction + +The default run is intentionally heavy. A quick water smoke test is: + +```powershell +julia --project=. visualisation/make_window_convergence.jl --aberrator=none --max-windows=2 +``` + +Check the configuration without running simulation/reconstruction: + +```powershell +julia --project=. visualisation/make_window_convergence.jl --dry-run=true +``` + +## Outputs + +Outputs are written to: + +```text +visualisation/outputs/_window_convergence/ +``` + +The folder contains: + +- `data.jld2`: final cumulative volume, truth mask, threshold search results, + selected windows, and per-frame metrics +- `summary.json`: human-readable run summary +- `frames/frame_0001.png`, etc. +- `pam_window_convergence.mp4` + +## Threshold Story + +The script first reconstructs all selected windows and computes the final +cumulative HASA volume. It searches thresholds from `0.10:0.01:0.95`, chooses +the threshold with the best final source F1, and freezes the corresponding +absolute intensity cutoff for every frame. + +Each frame therefore uses the same detection boundary. The orange region shows +the cumulative prediction above that fixed cutoff, white contours show the truth +mask, blue contours show the current-window contribution, and source points are +colored by detected versus not-yet-detected. + +## ffmpeg + +Install `ffmpeg` and make sure it is available on PATH to create the MP4. If it +is missing, the script still writes all PNG frames and prints the exact encoding +command. + +Useful options: + +```powershell +julia --project=. visualisation/make_window_convergence.jl ` + --out-dir=visualisation/outputs/test_run ` + --t-max-us=400 ` + --dy-mm=0.2 ` + --dz-mm=0.2 ` + --max-windows=0 ` + --fps=12 ` + --frames-only=false +``` diff --git a/visualisation/make_window_convergence.jl b/visualisation/make_window_convergence.jl new file mode 100644 index 0000000..f992ada --- /dev/null +++ b/visualisation/make_window_convergence.jl @@ -0,0 +1,720 @@ +#!/usr/bin/env julia + +using Pkg +Pkg.activate(joinpath(@__DIR__, "..")) + +using CairoMakie +using CUDA +using Dates +using JLD2 +using JSON3 +using Printf +using Random +using Statistics +using TranscranialFUS + +const PROJECT_ROOT = normpath(joinpath(@__DIR__, "..")) + +parse_bool(s) = lowercase(strip(String(s))) in ("1", "true", "yes", "on") + +function parse_cli(args) + opts = Dict{String, String}( + "out-dir" => "", + "random-seed" => "42", + "aberrator" => "skull", + "t-max-us" => "400", + "dy-mm" => "0.2", + "dz-mm" => "0.2", + "max-windows" => "0", + "fps" => "12", + "frames-only" => "false", + "dry-run" => "false", + "recon-progress" => "false", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", + "zero-pad-factor" => "2", + ) + for arg in args + startswith(arg, "--") || error("Unsupported argument format: $arg") + parts = split(arg[3:end], "="; limit=2) + length(parts) == 2 || error("Arguments must use --name=value, got: $arg") + opts[parts[1]] = parts[2] + end + return opts +end + +function timestamp() + return Dates.format(Dates.now(), "yyyymmdd_HHMMSS") +end + +function parse_aberrator(value::AbstractString) + sym = Symbol(lowercase(strip(value))) + sym in (:none, :water, :skull) || error("--aberrator must be none, water, or skull.") + return sym == :water ? :none : sym +end + +function source_summary_3d(src) + if src isa BubbleCluster3D + return Dict( + "type" => "BubbleCluster3D", + "depth_m" => src.depth, + "lateral_y_m" => src.lateral_y, + "lateral_z_m" => src.lateral_z, + "fundamental_hz" => src.fundamental, + "harmonics" => src.harmonics, + "amplitude" => src.amplitude, + ) + elseif src isa PointSource3D + return Dict( + "type" => "PointSource3D", + "depth_m" => src.depth, + "lateral_y_m" => src.lateral_y, + "lateral_z_m" => src.lateral_z, + "frequency_hz" => src.frequency, + "amplitude" => src.amplitude, + ) + end + return Dict("type" => string(typeof(src))) +end + +function make_demo_config(opts) + dy = parse(Float64, opts["dy-mm"]) * 1e-3 + dz = parse(Float64, opts["dz-mm"]) * 1e-3 + return PAMConfig3D( + dx = 0.2e-3, + dy = dy, + dz = dz, + axial_dim = 70e-3, + transverse_dim_y = 64e-3, + transverse_dim_z = 64e-3, + dt = 40e-9, + t_max = parse(Float64, opts["t-max-us"]) * 1e-6, + receiver_aperture_y = nothing, + receiver_aperture_z = nothing, + zero_pad_factor = parse(Int, opts["zero-pad-factor"]), + peak_suppression_radius = 2e-3, + success_tolerance = 1e-3, + axial_gain_power = 1.5, + ) +end + +function make_demo_sources(cfg::PAMConfig3D, seed::Integer) + rng = Random.MersenneTwister(seed) + centers = [(45e-3, 0.0, 0.0)] + sources, meta = make_network_bubble_sources_3d( + centers; + axial_radius = 10e-3, + lateral_y_radius = 1.5e-3, + lateral_z_radius = 1.5e-3, + root_count = 12, + generations = 3, + branch_length = 5.0e-3, + branch_step = 0.4e-3, + branch_angle = 36 * pi / 180, + tortuosity = 0.18, + network_orientation = :isotropic, + source_spacing = 0.5e-3, + density_sigma_depth = 10.0e-3, + density_sigma_y = 1.5e-3, + density_sigma_z = 1.5e-3, + min_separation = 0.25e-3, + max_sources_per_center = 80, + depth_bounds = (0.0, cfg.axial_dim), + lateral_y_bounds = (-cfg.transverse_dim_y / 2, cfg.transverse_dim_y / 2), + lateral_z_bounds = (-cfg.transverse_dim_z / 2, cfg.transverse_dim_z / 2), + fundamental = 0.5e6, + harmonics = [2, 3, 4], + harmonic_amplitudes = [1.0, 0.6, 0.3], + gate_duration = 50e-6, + taper_ratio = 0.25, + phase_mode = :geometric, + transducer_depth = -30e-3, + rng = rng, + ) + return sources, meta +end + +function default_recon_frequencies(sources) + freqs = Float64[] + for src in sources + append!(freqs, emission_frequencies(src)) + end + return sort(unique(freqs)) +end + +function source_detected_flags_3d(pred, grid, cfg::PAMConfig3D, sources; radius::Real) + radius_m = Float64(radius) + x = collect(grid.x) + y = collect(grid.y) + z = collect(grid.z) + r0 = receiver_row(cfg) + row_r = ceil(Int, radius_m / cfg.dx) + col_r_y = ceil(Int, radius_m / cfg.dy) + col_r_z = ceil(Int, radius_m / cfg.dz) + radius2 = radius_m^2 + + flags = falses(length(sources)) + distances_mm = Float64[] + for (idx, src) in pairs(sources) + src_x = x[r0] + src.depth + row0 = r0 + round(Int, src.depth / cfg.dx) + col0_y = argmin(abs.(y .- src.lateral_y)) + col0_z = argmin(abs.(z .- src.lateral_z)) + best_d2 = Inf + for row in max(r0 + 1, row0 - row_r):min(size(pred, 1), row0 + row_r) + dx2 = (x[row] - src_x)^2 + for iy in max(1, col0_y - col_r_y):min(size(pred, 2), col0_y + col_r_y) + dy2 = (y[iy] - src.lateral_y)^2 + for iz in max(1, col0_z - col_r_z):min(size(pred, 3), col0_z + col_r_z) + pred[row, iy, iz] || continue + d2 = dx2 + dy2 + (z[iz] - src.lateral_z)^2 + if d2 <= radius2 && d2 < best_d2 + best_d2 = d2 + end + end + end + end + if isfinite(best_d2) + flags[idx] = true + push!(distances_mm, sqrt(best_d2) * 1e3) + end + end + return flags, distances_mm +end + +function fixed_threshold_stats_3d(intensity, cutoff::Real, truth_mask, grid, cfg, sources; truth_radius::Real) + pred = intensity .>= Float64(cutoff) + tp = count(pred .& truth_mask) + fp = count(pred .& .!truth_mask) + fn = count(.!pred .& truth_mask) + precision = tp + fp == 0 ? 0.0 : tp / (tp + fp) + voxel_recall = tp + fn == 0 ? 0.0 : tp / (tp + fn) + voxel_f1 = precision + voxel_recall == 0 ? 0.0 : 2 * precision * voxel_recall / (precision + voxel_recall) + flags, distances_mm = source_detected_flags_3d(pred, grid, cfg, sources; radius=truth_radius) + detected = count(identity, flags) + source_recall = isempty(sources) ? 0.0 : detected / length(sources) + source_f1 = precision + source_recall == 0 ? 0.0 : 2 * precision * source_recall / (precision + source_recall) + return Dict{Symbol, Any}( + :source_f1 => source_f1, + :voxel_f1 => voxel_f1, + :precision => precision, + :source_recall => source_recall, + :voxel_recall => voxel_recall, + :detected_source_count => detected, + :num_truth_sources => length(sources), + :predicted_voxels => count(pred), + :true_positive_voxels => tp, + :false_positive_voxels => fp, + :false_negative_voxels => fn, + :truth_voxels => count(truth_mask), + :mean_detected_source_distance_mm => isempty(distances_mm) ? nothing : mean(distances_mm), + :max_detected_source_distance_mm => isempty(distances_mm) ? nothing : maximum(distances_mm), + :detected_flags => flags, + ) +end + +function best_final_threshold(final_intensity, truth_mask, grid, cfg, sources; truth_radius::Real) + local_ref = max(maximum(Float64.(final_intensity)), eps(Float64)) + thresholds = collect(0.10:0.01:0.95) + entries = Dict{Symbol, Any}[] + for ratio in thresholds + cutoff = Float64(ratio) * local_ref + entry = fixed_threshold_stats_3d(final_intensity, cutoff, truth_mask, grid, cfg, sources; truth_radius=truth_radius) + entry[:threshold_ratio] = Float64(ratio) + entry[:absolute_cutoff] = cutoff + push!(entries, entry) + end + best = first(entries) + for entry in entries[2:end] + score = (Float64(entry[:source_f1]), Float64(entry[:precision]), Float64(entry[:threshold_ratio])) + best_score = (Float64(best[:source_f1]), Float64(best[:precision]), Float64(best[:threshold_ratio])) + score > best_score && (best = entry) + end + return best, entries +end + +function qualify_windows(rf, cfg, window_config, max_windows::Integer) + nt = size(rf, 3) + ranges, window_samples, hop_samples = TranscranialFUS._pam_window_ranges(nt, cfg.dt, window_config) + energies = [sum(abs2, @view rf[:, :, range]) for range in ranges] + max_energy = isempty(energies) ? 0.0 : maximum(energies) + threshold = max_energy * window_config.min_energy_ratio + selected = UnitRange{Int}[] + selected_energy = Float64[] + skipped = UnitRange{Int}[] + for (range, energy) in zip(ranges, energies) + if energy < threshold || energy <= 0 + push!(skipped, range) + else + push!(selected, range) + push!(selected_energy, Float64(energy)) + end + end + if max_windows > 0 && length(selected) > max_windows + selected = selected[1:max_windows] + selected_energy = selected_energy[1:max_windows] + end + return selected, selected_energy, skipped, window_samples, hop_samples, threshold +end + +function reconstruct_one_window(rf, c, cfg, range, window_config, recon_frequencies, bandwidth_hz; + use_gpu::Bool, show_progress::Bool) + taper = TranscranialFUS._pam_temporal_taper(length(range), window_config.taper) + rf_window = Float64.(@view rf[:, :, range]) .* reshape(taper, 1, 1, :) + t0 = Float64(first(range) - 1) * cfg.dt + intensity, grid, _ = reconstruct_pam_3d( + rf_window, + c, + cfg; + frequencies = recon_frequencies, + bandwidth = bandwidth_hz, + corrected = true, + axial_step = 50e-6, + time_origin = t0, + use_gpu = use_gpu, + show_progress = show_progress, + window_batch = 1, + ) + return intensity, grid +end + +depth_mm(grid, cfg) = (collect(grid.x) .- grid.x[receiver_row(cfg)]) .* 1e3 +y_mm(grid) = collect(grid.y) .* 1e3 +z_mm(grid) = collect(grid.z) .* 1e3 + +function mask_projection(mask, projection::Symbol) + if projection == :depth_y + return dropdims(any(mask; dims=3); dims=3) + elseif projection == :depth_z + return dropdims(any(mask; dims=2); dims=2) + elseif projection == :y_z + return dropdims(any(mask; dims=1); dims=1) + end + error("Unknown projection: $projection") +end + +function volume_projection(volume, projection::Symbol) + if projection == :depth_y + return dropdims(maximum(volume; dims=3); dims=3) + elseif projection == :depth_z + return dropdims(maximum(volume; dims=2); dims=2) + elseif projection == :y_z + return dropdims(maximum(volume; dims=1); dims=1) + end + error("Unknown projection: $projection") +end + +function projection_axes(grid, cfg, projection::Symbol) + if projection == :depth_y + return depth_mm(grid, cfg), y_mm(grid), "Depth [mm]", "Y [mm]" + elseif projection == :depth_z + return depth_mm(grid, cfg), z_mm(grid), "Depth [mm]", "Z [mm]" + elseif projection == :y_z + return y_mm(grid), z_mm(grid), "Y [mm]", "Z [mm]" + end + error("Unknown projection: $projection") +end + +function normalized_projection(volume, projection::Symbol) + proj = Float64.(volume_projection(volume, projection)) + ref = max(maximum(proj), eps(Float64)) + return log10.(1 .+ 99 .* (proj ./ ref)) ./ 2 +end + +function add_contour_if_valid!(ax, xs, ys, mask; color, linewidth=2.0, linestyle=:solid) + any(mask) || return + any(.!mask) || return + contour!(ax, xs, ys, Float64.(mask); levels=[0.5], color=color, linewidth=linewidth, linestyle=linestyle) +end + +function threshold_voxel_points(mask, intensity, grid, cfg; max_points::Int=25000) + idxs = findall(mask) + isempty(idxs) && return Float64[], Float64[], Float64[], Float64[] + if length(idxs) > max_points + keep = unique(round.(Int, range(1, length(idxs); length=max_points))) + idxs = idxs[keep] + end + rr = receiver_row(cfg) + xs = Float64[] + ys = Float64[] + zs = Float64[] + cs = Float64[] + max_i = max(maximum(Float64.(intensity)), eps(Float64)) + sizehint!(xs, length(idxs)) + sizehint!(ys, length(idxs)) + sizehint!(zs, length(idxs)) + sizehint!(cs, length(idxs)) + for idx in idxs + push!(xs, grid.y[idx[2]] * 1e3) + push!(ys, grid.z[idx[3]] * 1e3) + push!(zs, (grid.x[idx[1]] - grid.x[rr]) * 1e3) + push!(cs, Float64(intensity[idx]) / max_i) + end + return xs, ys, zs, cs +end + +function render_frame(path, cumulative, current, truth_mask, fixed_cutoff, best_ratio, grid, cfg, sources, centerlines, stats, frame_idx, total_frames) + pred_mask = cumulative .>= fixed_cutoff + current_mask = current .>= fixed_cutoff + flags = stats[:detected_flags] + + update_theme!(fontsize=15) + fig = Figure(size=(1600, 950), backgroundcolor=:black) + + ax3 = Axis3( + fig[1:3, 1:2]; + xlabel="Y [mm]", + ylabel="Z [mm]", + zlabel="Depth [mm]", + title="3D cumulative HASA detection", + aspect=:data, + perspectiveness=0.35, + azimuth=5pi / 8, + elevation=pi / 7, + backgroundcolor=:black, + titlecolor=:white, + xlabelcolor=:white, + ylabelcolor=:white, + zlabelcolor=:white, + xticklabelcolor=:white, + yticklabelcolor=:white, + zticklabelcolor=:white, + ) + + for line in centerlines + ys = [p[2] * 1e3 for p in line] + zs = [p[3] * 1e3 for p in line] + ds = [p[1] * 1e3 for p in line] + lines!(ax3, ys, zs, ds; color=(:white, 0.55), linewidth=1.1) + end + + vx, vy, vz, vc = threshold_voxel_points(pred_mask, cumulative, grid, cfg; max_points=22000) + if !isempty(vx) + scatter!(ax3, vx, vy, vz; color=vc, colormap=:Oranges, colorrange=(0.0, 1.0), markersize=2.2, alpha=0.28) + end + + src_y = [src.lateral_y * 1e3 for src in sources] + src_z = [src.lateral_z * 1e3 for src in sources] + src_d = [src.depth * 1e3 for src in sources] + src_colors = [flags[i] ? :lime : (:gray80, 0.45) for i in eachindex(sources)] + scatter!(ax3, src_y, src_z, src_d; color=src_colors, markersize=8, strokecolor=:black, strokewidth=0.7) + + projections = [ + (:depth_y, "Depth-Y MIP"), + (:depth_z, "Depth-Z MIP"), + (:y_z, "Y-Z MIP"), + ] + for (col, (projection, title)) in enumerate(projections) + xs, ys, xlabel, ylabel = projection_axes(grid, cfg, projection) + ax = Axis( + fig[1, col + 2]; + title=title, + xlabel=xlabel, + ylabel=ylabel, + aspect=DataAspect(), + backgroundcolor=:black, + titlecolor=:white, + xlabelcolor=:white, + ylabelcolor=:white, + xticklabelcolor=:white, + yticklabelcolor=:white, + ) + heatmap!(ax, xs, ys, normalized_projection(cumulative, projection); colormap=:inferno, colorrange=(0, 1)) + add_contour_if_valid!(ax, xs, ys, mask_projection(truth_mask, projection); color=(:white, 0.9), linewidth=2.0, linestyle=:dash) + add_contour_if_valid!(ax, xs, ys, mask_projection(pred_mask, projection); color=(:orange, 0.95), linewidth=2.2) + add_contour_if_valid!(ax, xs, ys, mask_projection(current_mask, projection); color=(:deepskyblue, 0.75), linewidth=1.5) + end + + stats_text = @sprintf( + "window %d / %d\nfixed threshold: %.2f of final max\nsource F1: %.3f\nprecision: %.3f\nsource recall: %.3f\ndetected: %d / %d\npredicted voxels: %d", + frame_idx, + total_frames, + best_ratio, + Float64(stats[:source_f1]), + Float64(stats[:precision]), + Float64(stats[:source_recall]), + Int(stats[:detected_source_count]), + Int(stats[:num_truth_sources]), + Int(stats[:predicted_voxels]), + ) + Label( + fig[2:3, 3:5], + stats_text; + color=:white, + fontsize=24, + halign=:left, + valign=:top, + tellheight=false, + tellwidth=false, + ) + + Legend( + fig[4, 1:5], + [ + LineElement(color=(:white, 0.9), linestyle=:dash, linewidth=2), + LineElement(color=(:orange, 0.95), linewidth=3), + LineElement(color=(:deepskyblue, 0.75), linewidth=2), + MarkerElement(color=:lime, marker=:circle, markersize=12), + MarkerElement(color=(:gray80, 0.45), marker=:circle, markersize=12), + ], + ["truth mask", "cumulative prediction", "current window", "detected source", "not yet detected"]; + orientation=:horizontal, + framevisible=false, + labelcolor=:white, + tellheight=true, + ) + + save(path, fig) + return path +end + +function encode_mp4(frames_dir, mp4_path, fps::Integer) + ffmpeg = Sys.which("ffmpeg") + pattern = joinpath(frames_dir, "frame_%04d.png") + if isnothing(ffmpeg) + println("ffmpeg not found on PATH. Frames are ready in: $frames_dir") + println("Encode with:") + println("ffmpeg -y -framerate $fps -i \"$pattern\" -vf format=yuv420p \"$mp4_path\"") + return false + end + cmd = Cmd([ffmpeg, "-y", "-framerate", string(fps), "-i", pattern, "-vf", "format=yuv420p", mp4_path]) + run(cmd) + return true +end + +function print_dry_run(opts, cfg, fitted_cfg, sources, out_dir, window_config) + nt = pam_Nt(fitted_cfg) + ranges, window_samples, hop_samples = TranscranialFUS._pam_window_ranges(nt, fitted_cfg.dt, window_config) + println("Dry run: PAM window convergence visualisation") + println(" output dir : $out_dir") + println(" aberrator : ", opts["aberrator"]) + println(" sources : ", length(sources)) + println(" grid : $(pam_Nx(fitted_cfg)) x $(pam_Ny(fitted_cfg)) x $(pam_Nz(fitted_cfg))") + println(" spacing mm : dx=$(fitted_cfg.dx * 1e3), dy=$(fitted_cfg.dy * 1e3), dz=$(fitted_cfg.dz * 1e3)") + println(" t_max us : ", fitted_cfg.t_max * 1e6) + println(" nt : $nt") + println(" windows : $(length(ranges))") + println(" window samples : $window_samples") + println(" hop samples : $hop_samples") + println(" recon freqs MHz : ", join(round.(default_recon_frequencies(sources) ./ 1e6; digits=3), ", ")) + println(" CUDA functional : ", CUDA.functional()) + println(" k-Wave available : ", kwave_available()) + println(" ffmpeg : ", something(Sys.which("ffmpeg"), "not found")) + return nothing +end + +function main() + opts = parse_cli(ARGS) + seed = parse(Int, opts["random-seed"]) + aberrator = parse_aberrator(opts["aberrator"]) + dry_run = parse_bool(opts["dry-run"]) + frames_only = parse_bool(opts["frames-only"]) + fps = parse(Int, opts["fps"]) + max_windows = parse(Int, opts["max-windows"]) + use_gpu_sim = parse_bool(opts["kwave-use-gpu"]) + use_gpu_recon = parse_bool(opts["recon-use-gpu"]) + show_progress = parse_bool(opts["recon-progress"]) + + out_dir = isempty(strip(opts["out-dir"])) ? + joinpath(@__DIR__, "outputs", "$(timestamp())_window_convergence") : + abspath(opts["out-dir"]) + frames_dir = joinpath(out_dir, "frames") + data_path = joinpath(out_dir, "data.jld2") + summary_path = joinpath(out_dir, "summary.json") + mp4_path = joinpath(out_dir, "pam_window_convergence.mp4") + + cfg_base = make_demo_config(opts) + sources, network_meta = make_demo_sources(cfg_base, seed) + cfg = fit_pam_config_3d( + cfg_base, + sources; + min_bottom_margin=10e-3, + reference_depth=aberrator == :skull ? 20e-3 : nothing, + ) + window_config = PAMWindowConfig( + enabled=true, + window_duration=40e-6, + hop=20e-6, + taper=:hann, + min_energy_ratio=0.001, + accumulation=:intensity, + ) + + if dry_run + print_dry_run(opts, cfg_base, cfg, sources, out_dir, window_config) + return nothing + end + + mkpath(frames_dir) + + println("Building medium...") + c, rho, medium_info = make_pam_medium_3d( + cfg; + aberrator=aberrator, + skull_to_transducer=20e-3, + slice_index_z=250, + ) + + println("Expanding random-phase-per-window source events...") + rng_sim = Random.MersenneTwister(seed + 1) + sim_sources, n_frames = TranscranialFUS._expand_sources_per_window( + sources, + window_config.window_duration, + window_config.hop, + cfg.t_max, + rng_sim; + variability=SourceVariabilityConfig(frequency_jitter_fraction=0.01), + ) + + println("Simulating RF data with $(length(sim_sources)) emission events...") + rf, grid, simulation_info = simulate_point_sources_3d(c, rho, sim_sources, cfg; use_gpu=use_gpu_sim) + + selected_ranges, selected_energy, skipped_ranges, window_samples, hop_samples, energy_threshold = + qualify_windows(rf, cfg, window_config, max_windows) + isempty(selected_ranges) && error("No qualifying windows were found.") + + recon_frequencies = default_recon_frequencies(sources) + bandwidth_hz = 40e3 + truth_radius = 1.0e-3 + truth_mask = pam_truth_mask_3d(sources, grid, cfg; radius=truth_radius) + centerlines = network_meta[:centerlines] + + println("Accumulating $(length(selected_ranges)) reconstructed windows to choose final threshold...") + cumulative_sum = zeros(Float64, pam_Nx(cfg), pam_Ny(cfg), pam_Nz(cfg)) + final_grid = grid + for (idx, range) in pairs(selected_ranges) + @printf(" accumulation window %d/%d samples %d:%d\n", idx, length(selected_ranges), first(range), last(range)) + current, final_grid = reconstruct_one_window( + rf, c, cfg, range, window_config, recon_frequencies, bandwidth_hz; + use_gpu=use_gpu_recon, + show_progress=show_progress, + ) + cumulative_sum .+= current + GC.gc(false) + CUDA.reclaim() + end + final_cumulative = cumulative_sum ./ length(selected_ranges) + best_threshold, threshold_entries = best_final_threshold( + final_cumulative, + truth_mask, + final_grid, + cfg, + sources; + truth_radius=truth_radius, + ) + fixed_cutoff = Float64(best_threshold[:absolute_cutoff]) + best_ratio = Float64(best_threshold[:threshold_ratio]) + @printf("Selected final threshold %.2f of final max: source F1 %.3f, precision %.3f, source recall %.3f\n", + best_ratio, + Float64(best_threshold[:source_f1]), + Float64(best_threshold[:precision]), + Float64(best_threshold[:source_recall]), + ) + + metrics_by_frame = Dict{Symbol, Any}[] + println("Rendering frames with fixed final threshold...") + fill!(cumulative_sum, 0.0) + for (idx, range) in pairs(selected_ranges) + @printf(" render window %d/%d\n", idx, length(selected_ranges)) + current, final_grid = reconstruct_one_window( + rf, c, cfg, range, window_config, recon_frequencies, bandwidth_hz; + use_gpu=use_gpu_recon, + show_progress=show_progress, + ) + cumulative_sum .+= current + cumulative = cumulative_sum ./ idx + stats = fixed_threshold_stats_3d(cumulative, fixed_cutoff, truth_mask, final_grid, cfg, sources; truth_radius=truth_radius) + stats[:frame_index] = idx + stats[:sample_range] = [first(range), last(range)] + push!(metrics_by_frame, copy(stats)) + frame_path = joinpath(frames_dir, @sprintf("frame_%04d.png", idx)) + render_frame( + frame_path, + cumulative, + current, + truth_mask, + fixed_cutoff, + best_ratio, + final_grid, + cfg, + sources, + centerlines, + stats, + idx, + length(selected_ranges), + ) + GC.gc(false) + CUDA.reclaim() + end + + summary = Dict( + "out_dir" => out_dir, + "data_path" => data_path, + "frames_dir" => frames_dir, + "mp4_path" => mp4_path, + "random_seed" => seed, + "aberrator" => String(aberrator), + "grid" => Dict( + "nx" => pam_Nx(cfg), + "ny" => pam_Ny(cfg), + "nz" => pam_Nz(cfg), + "nt" => pam_Nt(cfg), + "dx_m" => cfg.dx, + "dy_m" => cfg.dy, + "dz_m" => cfg.dz, + "t_max_s" => cfg.t_max, + "zero_pad_factor" => cfg.zero_pad_factor, + ), + "source_model" => "network3d", + "source_count" => length(sources), + "emission_event_count" => length(sim_sources), + "n_frames_from_source_expansion" => n_frames, + "windowing" => Dict( + "window_duration_s" => window_config.window_duration, + "hop_s" => window_config.hop, + "window_samples" => window_samples, + "hop_samples" => hop_samples, + "selected_window_count" => length(selected_ranges), + "skipped_window_count" => length(skipped_ranges), + "energy_threshold" => energy_threshold, + ), + "reconstruction" => Dict( + "frequencies_hz" => recon_frequencies, + "bandwidth_hz" => bandwidth_hz, + "axial_step_m" => 50e-6, + "use_gpu" => use_gpu_recon, + ), + "threshold" => Dict( + "mode" => "final_best_source_f1_fixed_absolute_cutoff", + "ratio_of_final_max" => best_ratio, + "absolute_cutoff" => fixed_cutoff, + "best_final_metrics" => best_threshold, + ), + "medium" => Dict(String(k) => v for (k, v) in medium_info), + "simulation" => Dict(String(k) => v for (k, v) in simulation_info), + "sources" => [source_summary_3d(src) for src in sources], + "metrics_by_frame" => metrics_by_frame, + ) + + println("Saving data bundle...") + selected_ranges_pairs = [[first(r), last(r)] for r in selected_ranges] + skipped_ranges_pairs = [[first(r), last(r)] for r in skipped_ranges] + @save data_path cfg sources network_meta medium_info simulation_info recon_frequencies bandwidth_hz truth_radius truth_mask final_cumulative best_threshold threshold_entries selected_ranges_pairs skipped_ranges_pairs metrics_by_frame + + open(summary_path, "w") do io + JSON3.pretty(io, summary) + end + + if frames_only + println("Frames written to $frames_dir") + else + encoded = encode_mp4(frames_dir, mp4_path, fps) + encoded && println("Saved MP4 to $mp4_path") + end + println("Done: $out_dir") + return nothing +end + +if abspath(PROGRAM_FILE) == @__FILE__ + main() +end From 4dbd10b84971e9d6b4aa095becc5987026d24b0c Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 17:40:33 +0200 Subject: [PATCH 07/19] refactor run pam scripty --- scripts/run_pam.jl | 1005 +--------------------- src/TranscranialFUS.jl | 2 +- src/pam.jl | 3 + src/pam/analysis3d.jl | 156 ++++ src/pam/setup/config.jl | 297 +++++++ src/pam/setup/medium.jl | 60 ++ src/pam/setup/sources.jl | 490 +++++++++++ test/runtests.jl | 42 + visualisation/README.md | 21 +- visualisation/make_window_convergence.jl | 162 +++- 10 files changed, 1190 insertions(+), 1048 deletions(-) create mode 100644 src/pam/setup/config.jl create mode 100644 src/pam/setup/medium.jl create mode 100644 src/pam/setup/sources.jl diff --git a/scripts/run_pam.jl b/scripts/run_pam.jl index e3632f8..e13dfd8 100644 --- a/scripts/run_pam.jl +++ b/scripts/run_pam.jl @@ -11,790 +11,15 @@ using CairoMakie using JLD2 using JSON3 using TranscranialFUS +import TranscranialFUS: parse_cli, slug_value, parse_bool, parse_dimension, parse_float_list, parse_int_list, + parse_threshold_ratios, parse_threshold_search_ratios, parse_source_model, parse_aberrator, + parse_sim_mode, parse_cavitation_model, parse_source_phase_mode, parse_source_variability, + source_variability_from_summary, parse_analysis_mode, resolve_reconstruction_mode, + make_window_config, parse_receiver_aperture_mm, parse_transducer_mm, parse_point_sources, + parse_point_sources_3d, parse_squiggle_sources_3d, parse_network_sources_3d, + parse_squiggle_sources, parse_sources, default_simulation_info, default_recon_frequencies, + analytic_rf_for_point_sources_3d -function parse_cli(args) - opts = Dict{String, String}( - "dimension" => "2", - "source-model" => "squiggle", - "sources-mm" => "30:0", - "anchors-mm" => "45:0", - "frequency-mhz" => "0.4", - "fundamental-mhz" => "0.5", - "amplitude-pa" => "1.0", - "source-amplitudes-pa" => "", - "source-frequencies-mhz" => "", - "phases-deg" => "", - "n-bubbles" => "10", - "num-cycles" => "4", - "harmonics" => "2,3,4", - "harmonic-amplitudes" => "1.0,0.6,0.3", - "cavitation-model" => "harmonic-cos", - "gate-us" => "50", - "taper-ratio" => "0.25", - "axial-mm" => "80", - "transverse-mm" => "102.4", - "dx-mm" => "0.2", - "dz-mm" => "0.2", - "dy-mm" => "", - "transverse-y-mm" => "", - "transverse-z-mm" => "", - "axial-gain-power" => "1.5", - "receiver-aperture-mm" => "full", - "receiver-aperture-y-mm" => "", - "receiver-aperture-z-mm" => "", - "t-max-us" => "500", - "dt-ns" => "20", - "zero-pad-factor" => "4", - "peak-suppression-radius-mm" => "8.0", - "success-tolerance-mm" => "1.5", - "aberrator" => "none", - "sim-mode" => "auto", - "ct-path" => DEFAULT_CT_PATH, - "slice-index" => "250", - "skull-transducer-distance-mm" => "30", - "bottom-margin-mm" => "10", - "hu-bone-thr" => "200", - "lens-depth-mm" => "12", - "lens-lateral-mm" => "0", - "lens-axial-radius-mm" => "3", - "lens-lateral-radius-mm" => "12", - "aberrator-c" => "1700", - "aberrator-rho" => "1150", - "kwave-use-gpu" => "true", - "recon-use-gpu" => "true", - "recon-bandwidth-khz" => "500", - "recon-step-um" => "50", - "recon-mode" => "auto", - "recon-window-us" => "20", - "recon-hop-us" => "10", - "recon-window-taper" => "hann", - "recon-min-window-energy-ratio" => "0.001", - "recon-progress" => "false", - "benchmark" => "false", - "window-batch" => "1", - "phase-mode" => "geometric", - "phase-jitter-rad" => "0.2", - "random-seed" => "42", - "source-phase-mode" => "random_phase_per_window", - "n-realizations" => "1", - "frequency-jitter-percent" => "1", - "transducer-mm" => "-30:0", - "delays-us" => "0", - "vascular-length-mm" => "12", - "vascular-squiggle-amplitude-mm" => "1.5", - "vascular-squiggle-amplitude-x-mm" => "1.0", - "vascular-squiggle-wavelength-mm" => "8", - "vascular-squiggle-slope" => "0.0", - "squiggle-phase-x-deg" => "90", - "vascular-source-spacing-mm" => "0.5", - "vascular-position-jitter-mm" => "0.05", - "vascular-min-separation-mm" => "0.25", - "vascular-max-sources-per-anchor" => "0", - "vascular-radius-mm" => "1.0", - "network-radius-mm" => "0", - "network-axial-radius-mm" => "10.0", - "network-lateral-y-radius-mm" => "1.5", - "network-lateral-z-radius-mm" => "1.5", - "network-root-count" => "12", - "network-generations" => "3", - "network-branch-length-mm" => "5.0", - "network-branch-step-mm" => "0.4", - "network-branch-angle-deg" => "36", - "network-tortuosity" => "0.18", - "network-orientation" => "isotropic", - "network-density-sigma-mm" => "0", - "network-density-axial-sigma-mm" => "10.0", - "network-density-lateral-y-sigma-mm" => "1.5", - "network-density-lateral-z-sigma-mm" => "1.5", - "network-max-sources-per-center" => "80", - "analysis-mode" => "auto", - "detection-threshold-ratio" => "0.2", - "boundary-threshold-ratios" => "0.5,0.55,0.6,0.65,0.7,0.75", - "auto-threshold-search" => "true", - "auto-threshold-min" => "0.10", - "auto-threshold-max" => "0.95", - "auto-threshold-step" => "0.01", - "peak-method" => "argmax", - "clean-loop-gain" => "0.1", - "clean-max-iter" => "500", - "clean-threshold-ratio" => "0.01", - "from-run-dir" => "", - ) - - provided_keys = Set{String}() - for arg in args - startswith(arg, "--") || error("Unsupported argument format: $arg") - parts = split(arg[3:end], "="; limit=2) - length(parts) == 2 || error("Arguments must use --name=value, got: $arg") - push!(provided_keys, parts[1]) - opts[parts[1]] = parts[2] - end - apply_model_defaults!(opts, provided_keys) - return opts, provided_keys -end - -slug_value(x; digits::Int=1) = replace(string(round(Float64(x); digits=digits)), "-" => "m", "." => "p") -parse_bool(s::AbstractString) = lowercase(strip(s)) in ("1", "true", "yes", "on") - -function parse_dimension(s::AbstractString) - value = strip(s) - value in ("2", "2d", "2D") && return 2 - value in ("3", "3d", "3D") && return 3 - error("--dimension must be 2 or 3, got: $s") -end - -function parse_float_list(spec::AbstractString) - isempty(strip(spec)) && return Float64[] - return [parse(Float64, strip(item)) for item in split(spec, ",") if !isempty(strip(item))] -end - -function parse_int_list(spec::AbstractString) - isempty(strip(spec)) && return Int[] - return [parse(Int, strip(item)) for item in split(spec, ",") if !isempty(strip(item))] -end - -function parse_threshold_ratios(spec::AbstractString) - ratios = parse_float_list(spec) - isempty(ratios) && error("At least one threshold ratio is required.") - all(r -> r > 0, ratios) || error("Threshold ratios must be positive.") - return sort(unique(ratios)) -end - -function parse_threshold_search_ratios(opts) - min_ratio = parse(Float64, opts["auto-threshold-min"]) - max_ratio = parse(Float64, opts["auto-threshold-max"]) - step = parse(Float64, opts["auto-threshold-step"]) - min_ratio > 0 || error("--auto-threshold-min must be positive.") - max_ratio >= min_ratio || error("--auto-threshold-max must be >= --auto-threshold-min.") - step > 0 || error("--auto-threshold-step must be positive.") - n = floor(Int, (max_ratio - min_ratio) / step + 1e-9) - ratios = [round(min_ratio + i * step; digits=6) for i in 0:n] - if isempty(ratios) || ratios[end] < max_ratio - 1e-9 - push!(ratios, round(max_ratio; digits=6)) - end - return sort(unique(ratios)) -end - -function parse_source_model(s::AbstractString) - value = Symbol(lowercase(strip(s))) - value in (:point, :squiggle, :network) || error("--source-model must be point, squiggle, or network, got: $s") - return value -end - -function apply_model_defaults!(opts, provided_keys::Set{String}) - dimension = parse_dimension(opts["dimension"]) - if dimension == 3 - !("source-model" in provided_keys) && (opts["source-model"] = "point") - !("sources-mm" in provided_keys) && (opts["sources-mm"] = "30:0:0") - !("anchors-mm" in provided_keys) && (opts["anchors-mm"] = "45:0:0") - !("vascular-squiggle-amplitude-x-mm" in provided_keys) && (opts["vascular-squiggle-amplitude-x-mm"] = "1.0") - !("squiggle-phase-x-deg" in provided_keys) && (opts["squiggle-phase-x-deg"] = "90") - !("frequency-mhz" in provided_keys) && (opts["frequency-mhz"] = "0.5") - !("recon-bandwidth-khz" in provided_keys) && (opts["recon-bandwidth-khz"] = "0") - !("receiver-aperture-mm" in provided_keys) && (opts["receiver-aperture-mm"] = "full") - !("dx-mm" in provided_keys) && (opts["dx-mm"] = "0.2") - !("dy-mm" in provided_keys) && (opts["dy-mm"] = "0.5") - !("dz-mm" in provided_keys) && (opts["dz-mm"] = "0.5") - !("axial-mm" in provided_keys) && (opts["axial-mm"] = "60") - !("transverse-mm" in provided_keys) && (opts["transverse-mm"] = "32") - !("dt-ns" in provided_keys) && (opts["dt-ns"] = "80") - !("t-max-us" in provided_keys) && (opts["t-max-us"] = "60") - !("zero-pad-factor" in provided_keys) && (opts["zero-pad-factor"] = "4") - !("num-cycles" in provided_keys) && (opts["num-cycles"] = "5") - !("phase-mode" in provided_keys) && (opts["phase-mode"] = "coherent") - !("recon-step-um" in provided_keys) && (opts["recon-step-um"] = "50") - end - source_model = parse_source_model(opts["source-model"]) - if dimension == 3 && source_model in (:squiggle, :network) - !("vascular-source-spacing-mm" in provided_keys) && (opts["vascular-source-spacing-mm"] = "0.5") - !("vascular-min-separation-mm" in provided_keys) && (opts["vascular-min-separation-mm"] = "0.25") - !("recon-bandwidth-khz" in provided_keys) && (opts["recon-bandwidth-khz"] = "40") - !("recon-window-us" in provided_keys) && (opts["recon-window-us"] = "40") - !("recon-hop-us" in provided_keys) && (opts["recon-hop-us"] = "20") - !("boundary-threshold-ratios" in provided_keys) && (opts["boundary-threshold-ratios"] = "0.5,0.55,0.6,0.65,0.7,0.75") - end - if source_model == :point - !("source-phase-mode" in provided_keys) && (opts["source-phase-mode"] = "coherent") - !("recon-bandwidth-khz" in provided_keys) && (opts["recon-bandwidth-khz"] = "0") - !("receiver-aperture-mm" in provided_keys) && (opts["receiver-aperture-mm"] = "50") - !("transverse-mm" in provided_keys) && (opts["transverse-mm"] = "60") - !("dt-ns" in provided_keys) && (opts["dt-ns"] = "40") - !("t-max-us" in provided_keys) && (opts["t-max-us"] = "60") - !("axial-mm" in provided_keys) && (opts["axial-mm"] = "60") - !("phase-mode" in provided_keys) && (opts["phase-mode"] = "coherent") - end - return opts -end - -function parse_aberrator(s::AbstractString) - value = Symbol(lowercase(strip(s))) - value in (:none, :water, :lens, :skull) || error("Unknown aberrator: $s") - return value -end - -function parse_sim_mode(s::AbstractString) - value = Symbol(lowercase(strip(s))) - value in (:auto, :analytic, :kwave) || error("Unknown --sim-mode: $s (must be auto, analytic, or kwave)") - value == :auto && return :kwave - return value -end - -function parse_cavitation_model(s::AbstractString) - value = Symbol(replace(lowercase(strip(s)), "-" => "_")) - value in (:harmonic_cos, :gaussian_pulse) || - error("--cavitation-model must be harmonic-cos or gaussian-pulse, got: $s") - return value -end - -function parse_source_phase_mode(s::AbstractString) - value = Symbol(replace(lowercase(strip(s)), "-" => "_")) - value in (:coherent, :random_static_phase, :random_phase_per_window, :random_phase_per_realization) || - error("--source-phase-mode must be coherent, random_static_phase, random_phase_per_window, or random_phase_per_realization, got: $s") - return value -end - -parse_source_variability(opts) = SourceVariabilityConfig( - frequency_jitter_fraction=parse(Float64, opts["frequency-jitter-percent"]) / 100.0, -) - -function source_variability_from_summary(summary) - if isnothing(summary) || !hasproperty(summary, :source_variability) - return SourceVariabilityConfig() - end - sv = summary.source_variability - if hasproperty(sv, :frequency_jitter_percent) - return SourceVariabilityConfig(frequency_jitter_fraction=Float64(sv.frequency_jitter_percent) / 100.0) - end - return SourceVariabilityConfig() -end - -function parse_analysis_mode(s::AbstractString, source_model::Symbol) - value = Symbol(lowercase(strip(s))) - value == :auto && return source_model in (:squiggle, :network) ? :detection : :localization - value in (:localization, :detection) || error("--analysis-mode must be auto, localization, or detection, got: $s") - return value -end - -resolve_reconstruction_mode(s::AbstractString, source_model::Symbol) = - TranscranialFUS.pam_reconstruction_mode(s, source_model) - -function parse_window_taper(s::AbstractString) - value = Symbol(replace(lowercase(strip(s)), "-" => "_")) - value in (:hann, :none, :rect, :rectangular, :tukey) || - error("--recon-window-taper must be hann, none, rectangular, or tukey, got: $s") - return value -end - -function make_window_config(opts, reconstruction_mode::Symbol) - return PAMWindowConfig( - enabled=reconstruction_mode == :windowed, - window_duration=parse(Float64, opts["recon-window-us"]) * 1e-6, - hop=parse(Float64, opts["recon-hop-us"]) * 1e-6, - taper=parse_window_taper(opts["recon-window-taper"]), - min_energy_ratio=parse(Float64, opts["recon-min-window-energy-ratio"]), - accumulation=:intensity, - ) -end - -function parse_receiver_aperture_mm(s::AbstractString) - value = lowercase(strip(s)) - value in ("none", "full", "all") && return nothing - return parse(Float64, value) * 1e-3 -end - -function parse_transducer_mm(s::AbstractString) - parts = split(strip(s), ":"; limit=2) - length(parts) == 2 || error("--transducer-mm must be depth_mm:lateral_mm, got: $s") - return parse(Float64, strip(parts[1])) * 1e-3, parse(Float64, strip(parts[2])) * 1e-3 -end - -point_pairs_m(points) = [[point[1], point[2]] for point in points] -centerlines_m(centerlines) = [point_pairs_m(line) for line in centerlines] - -function expand_source_values(values::Vector{Float64}, n::Int, default::Float64) - isempty(values) && return fill(default, n) - length(values) == 1 && return fill(values[1], n) - length(values) == n && return values - error("Per-source parameter list must have length 1 or match the number of sources ($n).") -end - -function parse_coordinate_pairs_mm(spec::AbstractString, option_name::AbstractString) - coord_tokens = [strip(token) for token in split(spec, ",") if !isempty(strip(token))] - 1 <= length(coord_tokens) <= 20 || error("Provide between 1 and 20 coordinates via --$option_name=depth:lateral,...") - pairs = Tuple{Float64, Float64}[] - for token in coord_tokens - parts = split(token, ":"; limit=2) - length(parts) == 2 || error("Each coordinate must be depth_mm:lateral_mm, got: $token") - push!(pairs, (parse(Float64, strip(parts[1])) * 1e-3, parse(Float64, strip(parts[2])) * 1e-3)) - end - return pairs -end - -function parse_coordinate_triples_mm(spec::AbstractString, option_name::AbstractString) - coord_tokens = [strip(token) for token in split(spec, ",") if !isempty(strip(token))] - 1 <= length(coord_tokens) <= 20 || error("Provide between 1 and 20 coordinates via --$option_name=depth:y:z,...") - triples = NTuple{3, Float64}[] - for token in coord_tokens - parts = split(token, ":"; limit=3) - length(parts) == 3 || error("3D coordinates must be depth:y:z in mm, got: $token") - push!(triples, ( - parse(Float64, strip(parts[1])) * 1e-3, - parse(Float64, strip(parts[2])) * 1e-3, - parse(Float64, strip(parts[3])) * 1e-3, - )) - end - return triples -end - -function parse_point_sources(opts) - coordinates = parse_coordinate_pairs_mm(opts["sources-mm"], "sources-mm") - n_sources = length(coordinates) - frequencies_mhz = expand_source_values( - parse_float_list(opts["source-frequencies-mhz"]), - n_sources, - parse(Float64, opts["frequency-mhz"]), - ) - amplitudes_pa = expand_source_values( - parse_float_list(opts["source-amplitudes-pa"]), - n_sources, - parse(Float64, opts["amplitude-pa"]), - ) - phases_deg = expand_source_values(parse_float_list(opts["phases-deg"]), n_sources, 0.0) - delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_sources, 0.0) - num_cycles = parse(Int, opts["num-cycles"]) - - phase_mode = lowercase(strip(opts["phase-mode"])) - phase_mode in ("coherent", "random", "jittered") || - error("Point --phase-mode must be coherent, random, or jittered, got: $phase_mode") - rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) - if phase_mode == "random" - phases_deg = rand(rng, n_sources) .* 360.0 - elseif phase_mode == "jittered" - phases_deg = phases_deg .+ randn(rng, n_sources) .* (parse(Float64, opts["phase-jitter-rad"]) * 180 / pi) - end - - sources = EmissionSource2D[] - for (idx, (depth_m, lateral_m)) in pairs(coordinates) - push!(sources, PointSource2D( - depth=depth_m, - lateral=lateral_m, - frequency=frequencies_mhz[idx] * 1e6, - amplitude=amplitudes_pa[idx], - phase=phases_deg[idx] * pi / 180, - delay=delays_us[idx] * 1e-6, - num_cycles=num_cycles, - )) - end - return sources, Dict{String, Any}( - "source_model" => "point", - "coordinates_m" => [collect(coord) for coord in coordinates], - "n_coordinate_sources" => n_sources, - "n_emission_sources" => length(sources), - "physical_source_count" => length(sources), - "emission_event_count" => length(sources), - "activity_model" => Dict("activity_mode" => "point_tone_burst"), - "phase_mode" => phase_mode, - "frequencies_hz" => frequencies_mhz .* 1e6, - "amplitudes_pa" => amplitudes_pa, - "phases_rad" => phases_deg .* pi ./ 180, - "delays_s" => delays_us .* 1e-6, - "num_cycles" => num_cycles, - "random_seed" => parse(Int, opts["random-seed"]), - ) -end - -function parse_point_sources_3d(opts) - coordinates = parse_coordinate_triples_mm(opts["sources-mm"], "sources-mm") - n_sources = length(coordinates) - frequencies_mhz = expand_source_values( - parse_float_list(opts["source-frequencies-mhz"]), - n_sources, - parse(Float64, opts["frequency-mhz"]), - ) - amplitudes_pa = expand_source_values( - parse_float_list(opts["source-amplitudes-pa"]), - n_sources, - parse(Float64, opts["amplitude-pa"]), - ) - phases_deg = expand_source_values(parse_float_list(opts["phases-deg"]), n_sources, 0.0) - delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_sources, 0.0) - num_cycles = parse(Int, opts["num-cycles"]) - - phase_mode = lowercase(strip(opts["phase-mode"])) - phase_mode in ("coherent", "random", "jittered") || - error("Point --phase-mode must be coherent, random, or jittered, got: $phase_mode") - rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) - if phase_mode == "random" - phases_deg = rand(rng, n_sources) .* 360.0 - elseif phase_mode == "jittered" - phases_deg = phases_deg .+ randn(rng, n_sources) .* (parse(Float64, opts["phase-jitter-rad"]) * 180 / pi) - end - - sources = EmissionSource3D[] - for (idx, (depth_m, lateral_y_m, lateral_z_m)) in pairs(coordinates) - push!(sources, PointSource3D( - depth=depth_m, - lateral_y=lateral_y_m, - lateral_z=lateral_z_m, - frequency=frequencies_mhz[idx] * 1e6, - amplitude=amplitudes_pa[idx], - phase=phases_deg[idx] * pi / 180, - delay=delays_us[idx] * 1e-6, - num_cycles=num_cycles, - )) - end - return sources, Dict{String, Any}( - "source_model" => "point3d", - "coordinates_m" => [collect(coord) for coord in coordinates], - "n_coordinate_sources" => n_sources, - "n_emission_sources" => length(sources), - "physical_source_count" => length(sources), - "emission_event_count" => length(sources), - "activity_model" => Dict("activity_mode" => "point_tone_burst_3d"), - "phase_mode" => phase_mode, - "frequencies_hz" => frequencies_mhz .* 1e6, - "amplitudes_pa" => amplitudes_pa, - "phases_rad" => phases_deg .* pi ./ 180, - "delays_s" => delays_us .* 1e-6, - "num_cycles" => num_cycles, - "random_seed" => parse(Int, opts["random-seed"]), - ) -end - -centerlines_m_3d(centerlines) = [[[p[1], p[2], p[3]] for p in line] for line in centerlines] - -function parse_squiggle_sources_3d(opts, cfg::PAMConfig3D) - anchors = parse_coordinate_triples_mm(opts["anchors-mm"], "anchors-mm") - f0 = parse(Float64, opts["fundamental-mhz"]) * 1e6 - harmonics = parse_int_list(opts["harmonics"]) - isempty(harmonics) && error("--harmonics must be a non-empty integer list.") - harmonic_amplitudes = parse_float_list(opts["harmonic-amplitudes"]) - length(harmonic_amplitudes) == length(harmonics) || - error("--harmonic-amplitudes must have the same length as --harmonics ($(length(harmonics))).") - - n_anchors = length(anchors) - n_bubbles_per = expand_source_values(parse_float_list(opts["n-bubbles"]), n_anchors, 10.0) - delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_anchors, 0.0) - max_sources_raw = parse(Int, opts["vascular-max-sources-per-anchor"]) - max_sources = max_sources_raw <= 0 ? nothing : max_sources_raw - phase_mode = Symbol(replace(lowercase(strip(opts["phase-mode"])), "-" => "_")) - - sources = EmissionSource3D[] - all_centerlines_m = Any[] - anchors_meta = Dict{String, Any}[] - rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) - half_y = cfg.transverse_dim_y / 2 - half_z = cfg.transverse_dim_z / 2 - - for (idx, anchor) in pairs(anchors) - anchor_sources, anchor_meta = make_squiggle_bubble_sources_3d( - [anchor]; - root_length = parse(Float64, opts["vascular-length-mm"]) * 1e-3, - squiggle_amplitude_y = parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, - squiggle_amplitude_x = parse(Float64, opts["vascular-squiggle-amplitude-x-mm"]) * 1e-3, - squiggle_wavelength = parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, - squiggle_phase_x = parse(Float64, opts["squiggle-phase-x-deg"]) * pi / 180, - squiggle_slope_x = parse(Float64, opts["vascular-squiggle-slope"]), - squiggle_slope_y = 0.0, - source_spacing = parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, - position_jitter = parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, - min_separation = parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, - max_sources_per_anchor = max_sources, - depth_bounds = (0.0, Inf), - lateral_y_bounds = (-half_y, half_y), - lateral_z_bounds = (-half_z, half_z), - fundamental = f0, - amplitude = parse(Float64, opts["amplitude-pa"]), - n_bubbles = n_bubbles_per[idx], - harmonics = harmonics, - harmonic_amplitudes = harmonic_amplitudes, - gate_duration = parse(Float64, opts["gate-us"]) * 1e-6, - taper_ratio = parse(Float64, opts["taper-ratio"]), - delay = delays_us[idx] * 1e-6, - phase_mode = phase_mode, - phase_jitter = parse(Float64, opts["phase-jitter-rad"]), - transducer_depth = -parse(Float64, opts["skull-transducer-distance-mm"]) * 1e-3, - transducer_y = 0.0, - transducer_z = 0.0, - c0 = cfg.c0, - rng = rng, - ) - append!(sources, anchor_sources) - anchor_cls = centerlines_m_3d(anchor_meta[:centerlines]) - append!(all_centerlines_m, anchor_cls) - push!(anchors_meta, Dict( - "anchor_m" => collect(anchor), - "source_count" => length(anchor_sources), - "centerlines_m" => anchor_cls, - )) - end - - return sources, Dict{String, Any}( - "source_model" => "squiggle3d", - "anchor_clusters_m" => [collect(anchor) for anchor in anchors], - "n_anchor_clusters" => length(anchors), - "n_emission_sources" => length(sources), - "physical_source_count" => length(sources), - "emission_event_count" => length(sources), - "activity_model" => Dict("activity_mode" => "random_phase_per_window"), - "phase_mode" => String(phase_mode), - "fundamental_hz" => f0, - "harmonics" => harmonics, - "harmonic_amplitudes" => harmonic_amplitudes, - "gate_duration_s" => parse(Float64, opts["gate-us"]) * 1e-6, - "phase_jitter_rad" => parse(Float64, opts["phase-jitter-rad"]), - "random_seed" => parse(Int, opts["random-seed"]), - "n_bubbles_per_cluster" => n_bubbles_per, - "delays_s" => delays_us .* 1e-6, - "squiggle" => Dict( - "length_m" => parse(Float64, opts["vascular-length-mm"]) * 1e-3, - "squiggle_amplitude_y_m" => parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, - "squiggle_amplitude_x_m" => parse(Float64, opts["vascular-squiggle-amplitude-x-mm"]) * 1e-3, - "squiggle_wavelength_m" => parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, - "squiggle_phase_x_deg" => parse(Float64, opts["squiggle-phase-x-deg"]), - "squiggle_slope" => parse(Float64, opts["vascular-squiggle-slope"]), - "source_spacing_m" => parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, - "position_jitter_m" => parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, - "min_separation_m" => parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, - "max_sources_per_anchor" => max_sources_raw, - "truth_radius_m" => parse(Float64, opts["vascular-radius-mm"]) * 1e-3, - "centerlines_m" => all_centerlines_m, - "anchors" => anchors_meta, - ), - ) -end - -function parse_network_sources_3d(opts, cfg::PAMConfig3D) - centers = parse_coordinate_triples_mm(opts["anchors-mm"], "anchors-mm") - f0 = parse(Float64, opts["fundamental-mhz"]) * 1e6 - harmonics = parse_int_list(opts["harmonics"]) - isempty(harmonics) && error("--harmonics must be a non-empty integer list.") - harmonic_amplitudes = parse_float_list(opts["harmonic-amplitudes"]) - length(harmonic_amplitudes) == length(harmonics) || - error("--harmonic-amplitudes must have the same length as --harmonics ($(length(harmonics))).") - - n_centers = length(centers) - n_bubbles_per = expand_source_values(parse_float_list(opts["n-bubbles"]), n_centers, 1.0) - delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_centers, 0.0) - max_sources_raw = parse(Int, opts["network-max-sources-per-center"]) - max_sources = max_sources_raw <= 0 ? nothing : max_sources_raw - phase_mode = Symbol(replace(lowercase(strip(opts["phase-mode"])), "-" => "_")) - network_radius_m = parse(Float64, opts["network-radius-mm"]) * 1e-3 - axial_radius_m = parse(Float64, opts["network-axial-radius-mm"]) * 1e-3 - lateral_y_radius_m = parse(Float64, opts["network-lateral-y-radius-mm"]) * 1e-3 - lateral_z_radius_m = parse(Float64, opts["network-lateral-z-radius-mm"]) * 1e-3 - ellipsoid_radii_m = network_radius_m > 0 ? - [network_radius_m, network_radius_m, network_radius_m] : - [axial_radius_m, lateral_y_radius_m, lateral_z_radius_m] - density_sigma_m = parse(Float64, opts["network-density-sigma-mm"]) * 1e-3 - density_axial_sigma_m = parse(Float64, opts["network-density-axial-sigma-mm"]) * 1e-3 - density_lateral_y_sigma_m = parse(Float64, opts["network-density-lateral-y-sigma-mm"]) * 1e-3 - density_lateral_z_sigma_m = parse(Float64, opts["network-density-lateral-z-sigma-mm"]) * 1e-3 - density_sigmas_m = density_sigma_m > 0 ? - [density_sigma_m, density_sigma_m, density_sigma_m] : - [density_axial_sigma_m, density_lateral_y_sigma_m, density_lateral_z_sigma_m] - - sources = EmissionSource3D[] - all_centerlines_m = Any[] - centers_meta = Dict{String, Any}[] - rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) - half_y = cfg.transverse_dim_y / 2 - half_z = cfg.transverse_dim_z / 2 - - for (idx, center) in pairs(centers) - center_sources, network_meta = make_network_bubble_sources_3d( - [center]; - sphere_radius = network_radius_m, - axial_radius = axial_radius_m, - lateral_y_radius = lateral_y_radius_m, - lateral_z_radius = lateral_z_radius_m, - root_count = parse(Int, opts["network-root-count"]), - generations = parse(Int, opts["network-generations"]), - branch_length = parse(Float64, opts["network-branch-length-mm"]) * 1e-3, - branch_step = parse(Float64, opts["network-branch-step-mm"]) * 1e-3, - branch_angle = parse(Float64, opts["network-branch-angle-deg"]) * pi / 180, - tortuosity = parse(Float64, opts["network-tortuosity"]), - network_orientation = Symbol(replace(lowercase(strip(opts["network-orientation"])), "-" => "_")), - source_spacing = parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, - density_sigma = density_sigma_m, - density_sigma_depth = density_axial_sigma_m, - density_sigma_y = density_lateral_y_sigma_m, - density_sigma_z = density_lateral_z_sigma_m, - min_separation = parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, - max_sources_per_center = max_sources, - depth_bounds = (0.0, Inf), - lateral_y_bounds = (-half_y, half_y), - lateral_z_bounds = (-half_z, half_z), - fundamental = f0, - amplitude = parse(Float64, opts["amplitude-pa"]), - n_bubbles = n_bubbles_per[idx], - harmonics = harmonics, - harmonic_amplitudes = harmonic_amplitudes, - gate_duration = parse(Float64, opts["gate-us"]) * 1e-6, - taper_ratio = parse(Float64, opts["taper-ratio"]), - delay = delays_us[idx] * 1e-6, - phase_mode = phase_mode, - phase_jitter = parse(Float64, opts["phase-jitter-rad"]), - transducer_depth = -parse(Float64, opts["skull-transducer-distance-mm"]) * 1e-3, - transducer_y = 0.0, - transducer_z = 0.0, - c0 = cfg.c0, - rng = rng, - ) - append!(sources, center_sources) - center_cls = centerlines_m_3d(network_meta[:centerlines]) - append!(all_centerlines_m, center_cls) - push!(centers_meta, Dict( - "center_m" => collect(center), - "source_count" => length(center_sources), - "centerline_count" => length(network_meta[:centerlines]), - "centerlines_m" => center_cls, - )) - end - - return sources, Dict{String, Any}( - "source_model" => "network3d", - "network_centers_m" => [collect(center) for center in centers], - "n_network_centers" => length(centers), - "n_emission_sources" => length(sources), - "physical_source_count" => length(sources), - "emission_event_count" => length(sources), - "activity_model" => Dict("activity_mode" => "random_phase_per_window"), - "phase_mode" => String(phase_mode), - "fundamental_hz" => f0, - "harmonics" => harmonics, - "harmonic_amplitudes" => harmonic_amplitudes, - "gate_duration_s" => parse(Float64, opts["gate-us"]) * 1e-6, - "phase_jitter_rad" => parse(Float64, opts["phase-jitter-rad"]), - "random_seed" => parse(Int, opts["random-seed"]), - "n_bubbles_per_cluster" => n_bubbles_per, - "delays_s" => delays_us .* 1e-6, - "network" => Dict( - "radius_m" => network_radius_m, - "axial_radius_m" => axial_radius_m, - "lateral_y_radius_m" => lateral_y_radius_m, - "lateral_z_radius_m" => lateral_z_radius_m, - "ellipsoid_radii_m" => ellipsoid_radii_m, - "root_count" => parse(Int, opts["network-root-count"]), - "generations" => parse(Int, opts["network-generations"]), - "branch_length_m" => parse(Float64, opts["network-branch-length-mm"]) * 1e-3, - "branch_step_m" => parse(Float64, opts["network-branch-step-mm"]) * 1e-3, - "branch_angle_deg" => parse(Float64, opts["network-branch-angle-deg"]), - "tortuosity" => parse(Float64, opts["network-tortuosity"]), - "orientation" => opts["network-orientation"], - "density_sigma_m" => density_sigma_m, - "density_sigmas_m" => density_sigmas_m, - "source_spacing_m" => parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, - "min_separation_m" => parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, - "max_sources_per_center" => max_sources_raw, - "truth_radius_m" => parse(Float64, opts["vascular-radius-mm"]) * 1e-3, - "centerlines_m" => all_centerlines_m, - "centers" => centers_meta, - ), - ) -end - -function parse_squiggle_sources(opts, cfg::PAMConfig) - anchors = parse_coordinate_pairs_mm(opts["anchors-mm"], "anchors-mm") - f0 = parse(Float64, opts["fundamental-mhz"]) * 1e6 - harmonics = parse_int_list(opts["harmonics"]) - isempty(harmonics) && error("--harmonics must be a non-empty integer list.") - harmonic_amplitudes = parse_float_list(opts["harmonic-amplitudes"]) - length(harmonic_amplitudes) == length(harmonics) || - error("--harmonic-amplitudes must have the same length as --harmonics ($(length(harmonics))).") - - n_anchors = length(anchors) - n_bubbles_per = expand_source_values(parse_float_list(opts["n-bubbles"]), n_anchors, 10.0) - delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_anchors, 0.0) - tx_depth, tx_lateral = parse_transducer_mm(opts["transducer-mm"]) - max_sources_raw = parse(Int, opts["vascular-max-sources-per-anchor"]) - max_sources = max_sources_raw <= 0 ? nothing : max_sources_raw - phase_mode = Symbol(replace(lowercase(strip(opts["phase-mode"])), "-" => "_")) - - sources = EmissionSource2D[] - all_centerlines_m = Any[] - anchors_meta = Dict{String, Any}[] - rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) - for (idx, anchor) in pairs(anchors) - anchor_sources, anchor_meta = make_squiggle_bubble_sources( - [anchor]; - root_length=parse(Float64, opts["vascular-length-mm"]) * 1e-3, - squiggle_amplitude=parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, - squiggle_wavelength=parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, - squiggle_slope=parse(Float64, opts["vascular-squiggle-slope"]), - source_spacing=parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, - position_jitter=parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, - min_separation=parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, - max_sources_per_anchor=max_sources, - depth_bounds=(0.0, Inf), - lateral_bounds=(-cfg.transverse_dim / 2, cfg.transverse_dim / 2), - fundamental=f0, - amplitude=parse(Float64, opts["amplitude-pa"]), - n_bubbles=n_bubbles_per[idx], - harmonics=harmonics, - harmonic_amplitudes=harmonic_amplitudes, - cavitation_model=parse_cavitation_model(opts["cavitation-model"]), - gate_duration=parse(Float64, opts["gate-us"]) * 1e-6, - taper_ratio=parse(Float64, opts["taper-ratio"]), - delay=delays_us[idx] * 1e-6, - phase_mode=phase_mode, - phase_jitter=parse(Float64, opts["phase-jitter-rad"]), - transducer_depth=tx_depth, - transducer_lateral=tx_lateral, - c0=cfg.c0, - rng=rng, - ) - append!(sources, anchor_sources) - anchor_centerlines = centerlines_m(anchor_meta[:centerlines]) - append!(all_centerlines_m, anchor_centerlines) - push!(anchors_meta, Dict( - "anchor_m" => collect(anchor), - "source_count" => length(anchor_sources), - "centerlines_m" => anchor_centerlines, - )) - end - - return sources, Dict{String, Any}( - "source_model" => "squiggle", - "anchor_clusters_m" => [collect(anchor) for anchor in anchors], - "n_anchor_clusters" => length(anchors), - "n_emission_sources" => length(sources), - "physical_source_count" => length(sources), - "emission_event_count" => length(sources), - "activity_model" => Dict("activity_mode" => "random_phase_per_window"), - "phase_mode" => String(phase_mode), - "fundamental_hz" => f0, - "harmonics" => harmonics, - "harmonic_amplitudes" => harmonic_amplitudes, - "cavitation_model" => opts["cavitation-model"], - "gate_duration_s" => parse(Float64, opts["gate-us"]) * 1e-6, - "transducer_m" => [tx_depth, tx_lateral], - "phase_jitter_rad" => parse(Float64, opts["phase-jitter-rad"]), - "random_seed" => parse(Int, opts["random-seed"]), - "n_bubbles_per_cluster" => n_bubbles_per, - "delays_s" => delays_us .* 1e-6, - "squiggle" => Dict( - "length_m" => parse(Float64, opts["vascular-length-mm"]) * 1e-3, - "squiggle_amplitude_m" => parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, - "squiggle_wavelength_m" => parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, - "squiggle_slope" => parse(Float64, opts["vascular-squiggle-slope"]), - "source_spacing_m" => parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, - "position_jitter_m" => parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, - "min_separation_m" => parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, - "max_sources_per_anchor" => max_sources_raw, - "truth_radius_m" => parse(Float64, opts["vascular-radius-mm"]) * 1e-3, - "centerlines_m" => all_centerlines_m, - "anchors" => anchors_meta, - ), - ) -end - -function parse_sources(opts, cfg::PAMConfig) - source_model = parse_source_model(opts["source-model"]) - source_model == :point && return parse_point_sources(opts) - source_model == :squiggle && return parse_squiggle_sources(opts, cfg) - error("2D PAM CLI supports --source-model=point or --source-model=squiggle.") -end function default_output_dir(opts, sources, cfg, emission_meta) timestamp = Dates.format(Dates.now(), "yyyymmdd_HHMMSS") @@ -844,64 +69,6 @@ function reject_cached_simulation_options!(provided_keys::Set{String}, blocked_k error("--from-run-dir reuses the previous RF simulation, medium, sources, and grid. Remove simulation-specific option(s): $formatted") end -function default_simulation_info(cfg::PAMConfig) - return Dict{Symbol, Any}( - :receiver_row => receiver_row(cfg), - :receiver_cols => receiver_col_range(cfg), - :source_indices => Tuple{Int, Int}[], - ) -end - -function default_simulation_info(cfg::PAMConfig3D) - return Dict{Symbol, Any}( - :receiver_row => receiver_row(cfg), - :receiver_cols_y => receiver_col_range_y(cfg), - :receiver_cols_z => receiver_col_range_z(cfg), - :source_indices => NTuple{3, Int}[], - ) -end - -function default_recon_frequencies(sources) - freqs = Float64[] - for src in sources - append!(freqs, emission_frequencies(src)) - end - return sort(unique(freqs)) -end - -function _sample_source_signal(signal::AbstractVector{<:Real}, t::Real, dt::Real) - u = Float64(t) / Float64(dt) + 1.0 - i0 = floor(Int, u) - i0 < 1 && return 0.0 - i0 > length(signal) && return 0.0 - i0 == length(signal) && return Float64(signal[i0]) - frac = u - i0 - return (1.0 - frac) * Float64(signal[i0]) + frac * Float64(signal[i0 + 1]) -end - -function analytic_rf_for_point_sources_3d(cfg::PAMConfig3D, sources::AbstractVector{<:EmissionSource3D}) - grid = pam_grid_3d(cfg) - ny, nz, nt = pam_Ny(cfg), pam_Nz(cfg), pam_Nt(cfg) - rf = zeros(Float32, ny, nz, nt) - for src in sources - source_signal = TranscranialFUS._source_signal(nt, cfg.dt, src) - for iy in 1:ny, iz in 1:nz - dy_src = grid.y[iy] - src.lateral_y - dz_src = grid.z[iz] - src.lateral_z - r = sqrt(src.depth^2 + dy_src^2 + dz_src^2) - for it in 1:nt - emission_t = (it - 1) * cfg.dt - r / cfg.c0 - rf[iy, iz, it] += Float32(_sample_source_signal(source_signal, emission_t, cfg.dt)) - end - end - end - return rf, grid, Dict{Symbol, Any}( - :receiver_row => receiver_row(cfg), - :receiver_cols_y => receiver_col_range_y(cfg), - :receiver_cols_z => receiver_col_range_z(cfg), - :source_indices => [source_grid_index_3d(src, cfg) for src in sources], - ) -end function run_pam_case_3d( c::AbstractArray{<:Real, 3}, @@ -1165,162 +332,6 @@ function threshold_detection_stats(intensity, kgrid, cfg, sources; threshold_rat ] end -function source_detection_stats_3d(pred, grid, cfg::PAMConfig3D, sources; radius::Real) - radius_m = Float64(radius) - radius_m >= 0 || error("source detection radius must be non-negative.") - isempty(sources) && return Dict{Symbol, Any}( - :source_recall => 0.0, - :detected_source_count => 0, - :num_truth_sources => 0, - :mean_detected_source_distance_mm => nothing, - :max_detected_source_distance_mm => nothing, - ) - x = collect(grid.x) - y = collect(grid.y) - z = collect(grid.z) - r0 = receiver_row(cfg) - row_r = ceil(Int, radius_m / cfg.dx) - col_r_y = ceil(Int, radius_m / cfg.dy) - col_r_z = ceil(Int, radius_m / cfg.dz) - radius2 = radius_m^2 - - detected = 0 - distances_mm = Float64[] - for src in sources - src_x = x[r0] + src.depth - row0 = r0 + round(Int, src.depth / cfg.dx) - col0_y = argmin(abs.(y .- src.lateral_y)) - col0_z = argmin(abs.(z .- src.lateral_z)) - best_d2 = Inf - for row in max(r0 + 1, row0 - row_r):min(size(pred, 1), row0 + row_r) - dx2 = (x[row] - src_x)^2 - for iy in max(1, col0_y - col_r_y):min(size(pred, 2), col0_y + col_r_y) - dy2 = (y[iy] - src.lateral_y)^2 - for iz in max(1, col0_z - col_r_z):min(size(pred, 3), col0_z + col_r_z) - pred[row, iy, iz] || continue - d2 = dx2 + dy2 + (z[iz] - src.lateral_z)^2 - if d2 <= radius2 && d2 < best_d2 - best_d2 = d2 - end - end - end - end - if isfinite(best_d2) - detected += 1 - push!(distances_mm, sqrt(best_d2) * 1e3) - end - end - - return Dict{Symbol, Any}( - :source_recall => detected / length(sources), - :detected_source_count => detected, - :num_truth_sources => length(sources), - :mean_detected_source_distance_mm => isempty(distances_mm) ? nothing : mean(distances_mm), - :max_detected_source_distance_mm => isempty(distances_mm) ? nothing : maximum(distances_mm), - ) -end - -function threshold_detection_stats_3d(intensity, grid, cfg, sources; threshold_ratios, truth_radius, truth_mask) - truth = isnothing(truth_mask) ? pam_truth_mask_3d(sources, grid, cfg; radius=truth_radius) : truth_mask - local_ref = max(maximum(Float64.(intensity)), eps(Float64)) - return [ - begin - pred = intensity .>= ratio * local_ref - tp = count(pred .& truth) - fp = count(pred .& .!truth) - fn = count(.!pred .& truth) - precision = tp + fp == 0 ? 0.0 : tp / (tp + fp) - recall = tp + fn == 0 ? 0.0 : tp / (tp + fn) - f1 = precision + recall == 0 ? 0.0 : 2 * precision * recall / (precision + recall) - source_stats = source_detection_stats_3d(pred, grid, cfg, sources; radius=truth_radius) - source_recall = Float64(source_stats[:source_recall]) - source_f1 = precision + source_recall == 0 ? 0.0 : 2 * precision * source_recall / (precision + source_recall) - merge(Dict( - :threshold_ratio => ratio, - :f1 => source_f1, - :source_f1 => source_f1, - :voxel_f1 => f1, - :precision => precision, - :recall => source_recall, - :voxel_recall => recall, - :true_positive_voxels => tp, - :false_positive_voxels => fp, - :false_negative_voxels => fn, - :predicted_voxels => count(pred), - :truth_voxels => count(truth), - ), source_stats) - end - for ratio in threshold_ratios - ] -end - -function best_threshold_entry_3d(stats) - isempty(stats) && error("No 3D threshold stats available.") - best = first(stats) - for entry in stats[2:end] - score_metric = haskey(entry, :source_f1) ? :source_f1 : :f1 - best_metric = haskey(best, :source_f1) ? :source_f1 : :f1 - score = (Float64(entry[score_metric]), Float64(entry[:precision]), Float64(entry[:threshold_ratio])) - best_score = (Float64(best[best_metric]), Float64(best[:precision]), Float64(best[:threshold_ratio])) - if score > best_score - best = entry - end - end - return best -end - -_metric_value(entry, key::Symbol, fallback::Symbol=key) = Float64(get(entry, key, entry[fallback])) - -function _argmax_by(entries, scorefn) - best = first(entries) - best_score = scorefn(best) - for entry in entries[2:end] - score = scorefn(entry) - if score > best_score - best = entry - best_score = score - end - end - return best -end - -function _threshold_tradeoff_entry_3d(stats, best, target::Symbol) - best_f1 = _metric_value(best, :source_f1, :f1) - best_value = _metric_value(best, target, target == :source_recall ? :recall : target) - metric_key = target == :source_recall ? :source_recall : :precision - fallback_key = target == :source_recall ? :recall : :precision - candidates = [entry for entry in stats if _metric_value(entry, metric_key, fallback_key) > best_value + 1e-9] - for floor_fraction in (0.95, 0.90, 0.0) - viable = [entry for entry in candidates if _metric_value(entry, :source_f1, :f1) >= floor_fraction * best_f1] - isempty(viable) && continue - if target == :source_recall - return _argmax_by(viable, entry -> ( - _metric_value(entry, :source_recall, :recall), - _metric_value(entry, :source_f1, :f1), - _metric_value(entry, :precision), - )) - else - return _argmax_by(viable, entry -> ( - _metric_value(entry, :precision), - _metric_value(entry, :source_f1, :f1), - _metric_value(entry, :source_recall, :recall), - )) - end - end - return best -end - -function threshold_outline_entries_3d(stats) - best = best_threshold_entry_3d(stats) - recall = _threshold_tradeoff_entry_3d(stats, best, :source_recall) - precision = _threshold_tradeoff_entry_3d(stats, best, :precision) - return [ - (kind=:best_f1, label="best F1", color=:cyan, entry=best), - (kind=:more_recall, label="more recall", color=:lime, entry=recall), - (kind=:more_precision, label="more precision", color=:magenta, entry=precision), - ] -end - function overlay_skull_2d!(ax, c, xvals, yvals; transpose_matrix=true) skull_mask = skull_mask_from_c_columnwise(c; mask_outside=false) any(skull_mask) || return nothing diff --git a/src/TranscranialFUS.jl b/src/TranscranialFUS.jl index 12a8cef..68b006a 100644 --- a/src/TranscranialFUS.jl +++ b/src/TranscranialFUS.jl @@ -34,7 +34,7 @@ export EmissionSource3D, PointSource3D, BubbleCluster3D, make_squiggle_bubble_so export PAMConfig3D, pam_Nz, pam_grid_3d, receiver_col_range_y, receiver_col_range_z, depth_coordinates_3d, fit_pam_config_3d, source_grid_index_3d export make_pam_medium_3d export PAMCUDASetup3D, reconstruct_pam_3d, reconstruct_pam_windowed_3d -export find_pam_peaks_3d, pam_truth_mask_3d, analyse_pam_3d +export find_pam_peaks_3d, pam_truth_mask_3d, source_detection_stats_3d, threshold_detection_stats_3d, best_threshold_entry_3d, threshold_outline_entries_3d, analyse_pam_3d include("focus.jl") include("pam.jl") diff --git a/src/pam.jl b/src/pam.jl index c145087..9a32c92 100644 --- a/src/pam.jl +++ b/src/pam.jl @@ -11,4 +11,7 @@ include("pam/config3d.jl") include("pam/medium3d.jl") include("pam/reconstruction3d.jl") include("pam/analysis3d.jl") +include("pam/setup/config.jl") +include("pam/setup/sources.jl") +include("pam/setup/medium.jl") include("common/kwave_wrapper.jl") diff --git a/src/pam/analysis3d.jl b/src/pam/analysis3d.jl index 562de79..4aecef7 100644 --- a/src/pam/analysis3d.jl +++ b/src/pam/analysis3d.jl @@ -79,6 +79,162 @@ function pam_truth_mask_3d( return mask end +function source_detection_stats_3d(pred, grid, cfg::PAMConfig3D, sources; radius::Real) + radius_m = Float64(radius) + radius_m >= 0 || error("source detection radius must be non-negative.") + isempty(sources) && return Dict{Symbol, Any}( + :source_recall => 0.0, + :detected_source_count => 0, + :num_truth_sources => 0, + :mean_detected_source_distance_mm => nothing, + :max_detected_source_distance_mm => nothing, + ) + x = collect(grid.x) + y = collect(grid.y) + z = collect(grid.z) + r0 = receiver_row(cfg) + row_r = ceil(Int, radius_m / cfg.dx) + col_r_y = ceil(Int, radius_m / cfg.dy) + col_r_z = ceil(Int, radius_m / cfg.dz) + radius2 = radius_m^2 + + detected = 0 + distances_mm = Float64[] + for src in sources + src_x = x[r0] + src.depth + row0 = r0 + round(Int, src.depth / cfg.dx) + col0_y = argmin(abs.(y .- src.lateral_y)) + col0_z = argmin(abs.(z .- src.lateral_z)) + best_d2 = Inf + for row in max(r0 + 1, row0 - row_r):min(size(pred, 1), row0 + row_r) + dx2 = (x[row] - src_x)^2 + for iy in max(1, col0_y - col_r_y):min(size(pred, 2), col0_y + col_r_y) + dy2 = (y[iy] - src.lateral_y)^2 + for iz in max(1, col0_z - col_r_z):min(size(pred, 3), col0_z + col_r_z) + pred[row, iy, iz] || continue + d2 = dx2 + dy2 + (z[iz] - src.lateral_z)^2 + if d2 <= radius2 && d2 < best_d2 + best_d2 = d2 + end + end + end + end + if isfinite(best_d2) + detected += 1 + push!(distances_mm, sqrt(best_d2) * 1e3) + end + end + + return Dict{Symbol, Any}( + :source_recall => detected / length(sources), + :detected_source_count => detected, + :num_truth_sources => length(sources), + :mean_detected_source_distance_mm => isempty(distances_mm) ? nothing : mean(distances_mm), + :max_detected_source_distance_mm => isempty(distances_mm) ? nothing : maximum(distances_mm), + ) +end + +function threshold_detection_stats_3d(intensity, grid, cfg, sources; threshold_ratios, truth_radius, truth_mask) + truth = isnothing(truth_mask) ? pam_truth_mask_3d(sources, grid, cfg; radius=truth_radius) : truth_mask + local_ref = max(maximum(Float64.(intensity)), eps(Float64)) + return [ + begin + pred = intensity .>= ratio * local_ref + tp = count(pred .& truth) + fp = count(pred .& .!truth) + fn = count(.!pred .& truth) + precision = tp + fp == 0 ? 0.0 : tp / (tp + fp) + recall = tp + fn == 0 ? 0.0 : tp / (tp + fn) + f1 = precision + recall == 0 ? 0.0 : 2 * precision * recall / (precision + recall) + source_stats = source_detection_stats_3d(pred, grid, cfg, sources; radius=truth_radius) + source_recall = Float64(source_stats[:source_recall]) + source_f1 = precision + source_recall == 0 ? 0.0 : 2 * precision * source_recall / (precision + source_recall) + merge(Dict( + :threshold_ratio => ratio, + :f1 => source_f1, + :source_f1 => source_f1, + :voxel_f1 => f1, + :precision => precision, + :recall => source_recall, + :voxel_recall => recall, + :true_positive_voxels => tp, + :false_positive_voxels => fp, + :false_negative_voxels => fn, + :predicted_voxels => count(pred), + :truth_voxels => count(truth), + ), source_stats) + end + for ratio in threshold_ratios + ] +end + +function best_threshold_entry_3d(stats) + isempty(stats) && error("No 3D threshold stats available.") + best = first(stats) + for entry in stats[2:end] + score_metric = haskey(entry, :source_f1) ? :source_f1 : :f1 + best_metric = haskey(best, :source_f1) ? :source_f1 : :f1 + score = (Float64(entry[score_metric]), Float64(entry[:precision]), Float64(entry[:threshold_ratio])) + best_score = (Float64(best[best_metric]), Float64(best[:precision]), Float64(best[:threshold_ratio])) + if score > best_score + best = entry + end + end + return best +end + +_metric_value(entry, key::Symbol, fallback::Symbol=key) = Float64(get(entry, key, entry[fallback])) + +function _argmax_by(entries, scorefn) + best = first(entries) + best_score = scorefn(best) + for entry in entries[2:end] + score = scorefn(entry) + if score > best_score + best = entry + best_score = score + end + end + return best +end + +function _threshold_tradeoff_entry_3d(stats, best, target::Symbol) + best_f1 = _metric_value(best, :source_f1, :f1) + best_value = _metric_value(best, target, target == :source_recall ? :recall : target) + metric_key = target == :source_recall ? :source_recall : :precision + fallback_key = target == :source_recall ? :recall : :precision + candidates = [entry for entry in stats if _metric_value(entry, metric_key, fallback_key) > best_value + 1e-9] + for floor_fraction in (0.95, 0.90, 0.0) + viable = [entry for entry in candidates if _metric_value(entry, :source_f1, :f1) >= floor_fraction * best_f1] + isempty(viable) && continue + if target == :source_recall + return _argmax_by(viable, entry -> ( + _metric_value(entry, :source_recall, :recall), + _metric_value(entry, :source_f1, :f1), + _metric_value(entry, :precision), + )) + else + return _argmax_by(viable, entry -> ( + _metric_value(entry, :precision), + _metric_value(entry, :source_f1, :f1), + _metric_value(entry, :source_recall, :recall), + )) + end + end + return best +end + +function threshold_outline_entries_3d(stats) + best = best_threshold_entry_3d(stats) + recall = _threshold_tradeoff_entry_3d(stats, best, :source_recall) + precision = _threshold_tradeoff_entry_3d(stats, best, :precision) + return [ + (kind=:best_f1, label="best F1", color=:cyan, entry=best), + (kind=:more_recall, label="more recall", color=:lime, entry=recall), + (kind=:more_precision, label="more precision", color=:magenta, entry=precision), + ] +end + function analyse_pam_3d( intensity::AbstractArray{<:Real, 3}, grid::NamedTuple, diff --git a/src/pam/setup/config.jl b/src/pam/setup/config.jl new file mode 100644 index 0000000..582b46c --- /dev/null +++ b/src/pam/setup/config.jl @@ -0,0 +1,297 @@ +# CLI/config parsing helpers for PAM runner scripts. + +function parse_cli(args) + opts = Dict{String, String}( + "dimension" => "2", + "source-model" => "squiggle", + "sources-mm" => "30:0", + "anchors-mm" => "45:0", + "frequency-mhz" => "0.4", + "fundamental-mhz" => "0.5", + "amplitude-pa" => "1.0", + "source-amplitudes-pa" => "", + "source-frequencies-mhz" => "", + "phases-deg" => "", + "n-bubbles" => "10", + "num-cycles" => "4", + "harmonics" => "2,3,4", + "harmonic-amplitudes" => "1.0,0.6,0.3", + "cavitation-model" => "harmonic-cos", + "gate-us" => "50", + "taper-ratio" => "0.25", + "axial-mm" => "80", + "transverse-mm" => "102.4", + "dx-mm" => "0.2", + "dz-mm" => "0.2", + "dy-mm" => "", + "transverse-y-mm" => "", + "transverse-z-mm" => "", + "axial-gain-power" => "1.5", + "receiver-aperture-mm" => "full", + "receiver-aperture-y-mm" => "", + "receiver-aperture-z-mm" => "", + "t-max-us" => "500", + "dt-ns" => "20", + "zero-pad-factor" => "4", + "peak-suppression-radius-mm" => "8.0", + "success-tolerance-mm" => "1.5", + "aberrator" => "none", + "sim-mode" => "auto", + "ct-path" => DEFAULT_CT_PATH, + "slice-index" => "250", + "skull-transducer-distance-mm" => "30", + "bottom-margin-mm" => "10", + "hu-bone-thr" => "200", + "lens-depth-mm" => "12", + "lens-lateral-mm" => "0", + "lens-axial-radius-mm" => "3", + "lens-lateral-radius-mm" => "12", + "aberrator-c" => "1700", + "aberrator-rho" => "1150", + "kwave-use-gpu" => "true", + "recon-use-gpu" => "true", + "recon-bandwidth-khz" => "500", + "recon-step-um" => "50", + "recon-mode" => "auto", + "recon-window-us" => "20", + "recon-hop-us" => "10", + "recon-window-taper" => "hann", + "recon-min-window-energy-ratio" => "0.001", + "recon-progress" => "false", + "benchmark" => "false", + "window-batch" => "1", + "phase-mode" => "geometric", + "phase-jitter-rad" => "0.2", + "random-seed" => "42", + "source-phase-mode" => "random_phase_per_window", + "n-realizations" => "1", + "frequency-jitter-percent" => "1", + "transducer-mm" => "-30:0", + "delays-us" => "0", + "vascular-length-mm" => "12", + "vascular-squiggle-amplitude-mm" => "1.5", + "vascular-squiggle-amplitude-x-mm" => "1.0", + "vascular-squiggle-wavelength-mm" => "8", + "vascular-squiggle-slope" => "0.0", + "squiggle-phase-x-deg" => "90", + "vascular-source-spacing-mm" => "0.5", + "vascular-position-jitter-mm" => "0.05", + "vascular-min-separation-mm" => "0.25", + "vascular-max-sources-per-anchor" => "0", + "vascular-radius-mm" => "1.0", + "network-radius-mm" => "0", + "network-axial-radius-mm" => "10.0", + "network-lateral-y-radius-mm" => "1.5", + "network-lateral-z-radius-mm" => "1.5", + "network-root-count" => "12", + "network-generations" => "3", + "network-branch-length-mm" => "5.0", + "network-branch-step-mm" => "0.4", + "network-branch-angle-deg" => "36", + "network-tortuosity" => "0.18", + "network-orientation" => "isotropic", + "network-density-sigma-mm" => "0", + "network-density-axial-sigma-mm" => "10.0", + "network-density-lateral-y-sigma-mm" => "1.5", + "network-density-lateral-z-sigma-mm" => "1.5", + "network-max-sources-per-center" => "80", + "analysis-mode" => "auto", + "detection-threshold-ratio" => "0.2", + "boundary-threshold-ratios" => "0.5,0.55,0.6,0.65,0.7,0.75", + "auto-threshold-search" => "true", + "auto-threshold-min" => "0.10", + "auto-threshold-max" => "0.95", + "auto-threshold-step" => "0.01", + "peak-method" => "argmax", + "clean-loop-gain" => "0.1", + "clean-max-iter" => "500", + "clean-threshold-ratio" => "0.01", + "from-run-dir" => "", + ) + + provided_keys = Set{String}() + for arg in args + startswith(arg, "--") || error("Unsupported argument format: $arg") + parts = split(arg[3:end], "="; limit=2) + length(parts) == 2 || error("Arguments must use --name=value, got: $arg") + push!(provided_keys, parts[1]) + opts[parts[1]] = parts[2] + end + apply_model_defaults!(opts, provided_keys) + return opts, provided_keys +end + +slug_value(x; digits::Int=1) = replace(string(round(Float64(x); digits=digits)), "-" => "m", "." => "p") +parse_bool(s::AbstractString) = lowercase(strip(s)) in ("1", "true", "yes", "on") + +function parse_dimension(s::AbstractString) + value = strip(s) + value in ("2", "2d", "2D") && return 2 + value in ("3", "3d", "3D") && return 3 + error("--dimension must be 2 or 3, got: $s") +end + +function parse_float_list(spec::AbstractString) + isempty(strip(spec)) && return Float64[] + return [parse(Float64, strip(item)) for item in split(spec, ",") if !isempty(strip(item))] +end + +function parse_int_list(spec::AbstractString) + isempty(strip(spec)) && return Int[] + return [parse(Int, strip(item)) for item in split(spec, ",") if !isempty(strip(item))] +end + +function parse_threshold_ratios(spec::AbstractString) + ratios = parse_float_list(spec) + isempty(ratios) && error("At least one threshold ratio is required.") + all(r -> r > 0, ratios) || error("Threshold ratios must be positive.") + return sort(unique(ratios)) +end + +function parse_threshold_search_ratios(opts) + min_ratio = parse(Float64, opts["auto-threshold-min"]) + max_ratio = parse(Float64, opts["auto-threshold-max"]) + step = parse(Float64, opts["auto-threshold-step"]) + min_ratio > 0 || error("--auto-threshold-min must be positive.") + max_ratio >= min_ratio || error("--auto-threshold-max must be >= --auto-threshold-min.") + step > 0 || error("--auto-threshold-step must be positive.") + n = floor(Int, (max_ratio - min_ratio) / step + 1e-9) + ratios = [round(min_ratio + i * step; digits=6) for i in 0:n] + if isempty(ratios) || ratios[end] < max_ratio - 1e-9 + push!(ratios, round(max_ratio; digits=6)) + end + return sort(unique(ratios)) +end + +function parse_source_model(s::AbstractString) + value = Symbol(lowercase(strip(s))) + value in (:point, :squiggle, :network) || error("--source-model must be point, squiggle, or network, got: $s") + return value +end + +function apply_model_defaults!(opts, provided_keys::Set{String}) + dimension = parse_dimension(opts["dimension"]) + if dimension == 3 + !("source-model" in provided_keys) && (opts["source-model"] = "point") + !("sources-mm" in provided_keys) && (opts["sources-mm"] = "30:0:0") + !("anchors-mm" in provided_keys) && (opts["anchors-mm"] = "45:0:0") + !("vascular-squiggle-amplitude-x-mm" in provided_keys) && (opts["vascular-squiggle-amplitude-x-mm"] = "1.0") + !("squiggle-phase-x-deg" in provided_keys) && (opts["squiggle-phase-x-deg"] = "90") + !("frequency-mhz" in provided_keys) && (opts["frequency-mhz"] = "0.5") + !("recon-bandwidth-khz" in provided_keys) && (opts["recon-bandwidth-khz"] = "0") + !("receiver-aperture-mm" in provided_keys) && (opts["receiver-aperture-mm"] = "full") + !("dx-mm" in provided_keys) && (opts["dx-mm"] = "0.2") + !("dy-mm" in provided_keys) && (opts["dy-mm"] = "0.5") + !("dz-mm" in provided_keys) && (opts["dz-mm"] = "0.5") + !("axial-mm" in provided_keys) && (opts["axial-mm"] = "60") + !("transverse-mm" in provided_keys) && (opts["transverse-mm"] = "32") + !("dt-ns" in provided_keys) && (opts["dt-ns"] = "80") + !("t-max-us" in provided_keys) && (opts["t-max-us"] = "60") + !("zero-pad-factor" in provided_keys) && (opts["zero-pad-factor"] = "4") + !("num-cycles" in provided_keys) && (opts["num-cycles"] = "5") + !("phase-mode" in provided_keys) && (opts["phase-mode"] = "coherent") + !("recon-step-um" in provided_keys) && (opts["recon-step-um"] = "50") + end + source_model = parse_source_model(opts["source-model"]) + if dimension == 3 && source_model in (:squiggle, :network) + !("vascular-source-spacing-mm" in provided_keys) && (opts["vascular-source-spacing-mm"] = "0.5") + !("vascular-min-separation-mm" in provided_keys) && (opts["vascular-min-separation-mm"] = "0.25") + !("recon-bandwidth-khz" in provided_keys) && (opts["recon-bandwidth-khz"] = "40") + !("recon-window-us" in provided_keys) && (opts["recon-window-us"] = "40") + !("recon-hop-us" in provided_keys) && (opts["recon-hop-us"] = "20") + !("boundary-threshold-ratios" in provided_keys) && (opts["boundary-threshold-ratios"] = "0.5,0.55,0.6,0.65,0.7,0.75") + end + if source_model == :point + !("source-phase-mode" in provided_keys) && (opts["source-phase-mode"] = "coherent") + !("recon-bandwidth-khz" in provided_keys) && (opts["recon-bandwidth-khz"] = "0") + !("receiver-aperture-mm" in provided_keys) && (opts["receiver-aperture-mm"] = "50") + !("transverse-mm" in provided_keys) && (opts["transverse-mm"] = "60") + !("dt-ns" in provided_keys) && (opts["dt-ns"] = "40") + !("t-max-us" in provided_keys) && (opts["t-max-us"] = "60") + !("axial-mm" in provided_keys) && (opts["axial-mm"] = "60") + !("phase-mode" in provided_keys) && (opts["phase-mode"] = "coherent") + end + return opts +end + +function parse_aberrator(s::AbstractString) + value = Symbol(lowercase(strip(s))) + value in (:none, :water, :lens, :skull) || error("Unknown aberrator: $s") + return value +end + +function parse_sim_mode(s::AbstractString) + value = Symbol(lowercase(strip(s))) + value in (:auto, :analytic, :kwave) || error("Unknown --sim-mode: $s (must be auto, analytic, or kwave)") + value == :auto && return :kwave + return value +end + +function parse_cavitation_model(s::AbstractString) + value = Symbol(replace(lowercase(strip(s)), "-" => "_")) + value in (:harmonic_cos, :gaussian_pulse) || + error("--cavitation-model must be harmonic-cos or gaussian-pulse, got: $s") + return value +end + +function parse_source_phase_mode(s::AbstractString) + value = Symbol(replace(lowercase(strip(s)), "-" => "_")) + value in (:coherent, :random_static_phase, :random_phase_per_window, :random_phase_per_realization) || + error("--source-phase-mode must be coherent, random_static_phase, random_phase_per_window, or random_phase_per_realization, got: $s") + return value +end + +parse_source_variability(opts) = SourceVariabilityConfig( + frequency_jitter_fraction=parse(Float64, opts["frequency-jitter-percent"]) / 100.0, +) + +function source_variability_from_summary(summary) + if isnothing(summary) || !hasproperty(summary, :source_variability) + return SourceVariabilityConfig() + end + sv = summary.source_variability + if hasproperty(sv, :frequency_jitter_percent) + return SourceVariabilityConfig(frequency_jitter_fraction=Float64(sv.frequency_jitter_percent) / 100.0) + end + return SourceVariabilityConfig() +end + +function parse_analysis_mode(s::AbstractString, source_model::Symbol) + value = Symbol(lowercase(strip(s))) + value == :auto && return source_model in (:squiggle, :network) ? :detection : :localization + value in (:localization, :detection) || error("--analysis-mode must be auto, localization, or detection, got: $s") + return value +end + +resolve_reconstruction_mode(s::AbstractString, source_model::Symbol) = + TranscranialFUS.pam_reconstruction_mode(s, source_model) + +function parse_window_taper(s::AbstractString) + value = Symbol(replace(lowercase(strip(s)), "-" => "_")) + value in (:hann, :none, :rect, :rectangular, :tukey) || + error("--recon-window-taper must be hann, none, rectangular, or tukey, got: $s") + return value +end + +function make_window_config(opts, reconstruction_mode::Symbol) + return PAMWindowConfig( + enabled=reconstruction_mode == :windowed, + window_duration=parse(Float64, opts["recon-window-us"]) * 1e-6, + hop=parse(Float64, opts["recon-hop-us"]) * 1e-6, + taper=parse_window_taper(opts["recon-window-taper"]), + min_energy_ratio=parse(Float64, opts["recon-min-window-energy-ratio"]), + accumulation=:intensity, + ) +end + +function parse_receiver_aperture_mm(s::AbstractString) + value = lowercase(strip(s)) + value in ("none", "full", "all") && return nothing + return parse(Float64, value) * 1e-3 +end + +function parse_transducer_mm(s::AbstractString) + parts = split(strip(s), ":"; limit=2) + length(parts) == 2 || error("--transducer-mm must be depth_mm:lateral_mm, got: $s") + return parse(Float64, strip(parts[1])) * 1e-3, parse(Float64, strip(parts[2])) * 1e-3 +end diff --git a/src/pam/setup/medium.jl b/src/pam/setup/medium.jl new file mode 100644 index 0000000..2fc07e3 --- /dev/null +++ b/src/pam/setup/medium.jl @@ -0,0 +1,60 @@ +# Simulation defaults and lightweight analytic helpers for PAM runner scripts. + +function default_simulation_info(cfg::PAMConfig) + return Dict{Symbol, Any}( + :receiver_row => receiver_row(cfg), + :receiver_cols => receiver_col_range(cfg), + :source_indices => Tuple{Int, Int}[], + ) +end + +function default_simulation_info(cfg::PAMConfig3D) + return Dict{Symbol, Any}( + :receiver_row => receiver_row(cfg), + :receiver_cols_y => receiver_col_range_y(cfg), + :receiver_cols_z => receiver_col_range_z(cfg), + :source_indices => NTuple{3, Int}[], + ) +end + +function default_recon_frequencies(sources) + freqs = Float64[] + for src in sources + append!(freqs, emission_frequencies(src)) + end + return sort(unique(freqs)) +end + +function _sample_source_signal(signal::AbstractVector{<:Real}, t::Real, dt::Real) + u = Float64(t) / Float64(dt) + 1.0 + i0 = floor(Int, u) + i0 < 1 && return 0.0 + i0 > length(signal) && return 0.0 + i0 == length(signal) && return Float64(signal[i0]) + frac = u - i0 + return (1.0 - frac) * Float64(signal[i0]) + frac * Float64(signal[i0 + 1]) +end + +function analytic_rf_for_point_sources_3d(cfg::PAMConfig3D, sources::AbstractVector{<:EmissionSource3D}) + grid = pam_grid_3d(cfg) + ny, nz, nt = pam_Ny(cfg), pam_Nz(cfg), pam_Nt(cfg) + rf = zeros(Float32, ny, nz, nt) + for src in sources + source_signal = TranscranialFUS._source_signal(nt, cfg.dt, src) + for iy in 1:ny, iz in 1:nz + dy_src = grid.y[iy] - src.lateral_y + dz_src = grid.z[iz] - src.lateral_z + r = sqrt(src.depth^2 + dy_src^2 + dz_src^2) + for it in 1:nt + emission_t = (it - 1) * cfg.dt - r / cfg.c0 + rf[iy, iz, it] += Float32(_sample_source_signal(source_signal, emission_t, cfg.dt)) + end + end + end + return rf, grid, Dict{Symbol, Any}( + :receiver_row => receiver_row(cfg), + :receiver_cols_y => receiver_col_range_y(cfg), + :receiver_cols_z => receiver_col_range_z(cfg), + :source_indices => [source_grid_index_3d(src, cfg) for src in sources], + ) +end diff --git a/src/pam/setup/sources.jl b/src/pam/setup/sources.jl new file mode 100644 index 0000000..58d00ab --- /dev/null +++ b/src/pam/setup/sources.jl @@ -0,0 +1,490 @@ +# Source parsing and source metadata helpers for PAM runner scripts. + +point_pairs_m(points) = [[point[1], point[2]] for point in points] +centerlines_m(centerlines) = [point_pairs_m(line) for line in centerlines] + +function expand_source_values(values::Vector{Float64}, n::Int, default::Float64) + isempty(values) && return fill(default, n) + length(values) == 1 && return fill(values[1], n) + length(values) == n && return values + error("Per-source parameter list must have length 1 or match the number of sources ($n).") +end + +function parse_coordinate_pairs_mm(spec::AbstractString, option_name::AbstractString) + coord_tokens = [strip(token) for token in split(spec, ",") if !isempty(strip(token))] + 1 <= length(coord_tokens) <= 20 || error("Provide between 1 and 20 coordinates via --$option_name=depth:lateral,...") + pairs = Tuple{Float64, Float64}[] + for token in coord_tokens + parts = split(token, ":"; limit=2) + length(parts) == 2 || error("Each coordinate must be depth_mm:lateral_mm, got: $token") + push!(pairs, (parse(Float64, strip(parts[1])) * 1e-3, parse(Float64, strip(parts[2])) * 1e-3)) + end + return pairs +end + +function parse_coordinate_triples_mm(spec::AbstractString, option_name::AbstractString) + coord_tokens = [strip(token) for token in split(spec, ",") if !isempty(strip(token))] + 1 <= length(coord_tokens) <= 20 || error("Provide between 1 and 20 coordinates via --$option_name=depth:y:z,...") + triples = NTuple{3, Float64}[] + for token in coord_tokens + parts = split(token, ":"; limit=3) + length(parts) == 3 || error("3D coordinates must be depth:y:z in mm, got: $token") + push!(triples, ( + parse(Float64, strip(parts[1])) * 1e-3, + parse(Float64, strip(parts[2])) * 1e-3, + parse(Float64, strip(parts[3])) * 1e-3, + )) + end + return triples +end + +function parse_point_sources(opts) + coordinates = parse_coordinate_pairs_mm(opts["sources-mm"], "sources-mm") + n_sources = length(coordinates) + frequencies_mhz = expand_source_values( + parse_float_list(opts["source-frequencies-mhz"]), + n_sources, + parse(Float64, opts["frequency-mhz"]), + ) + amplitudes_pa = expand_source_values( + parse_float_list(opts["source-amplitudes-pa"]), + n_sources, + parse(Float64, opts["amplitude-pa"]), + ) + phases_deg = expand_source_values(parse_float_list(opts["phases-deg"]), n_sources, 0.0) + delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_sources, 0.0) + num_cycles = parse(Int, opts["num-cycles"]) + + phase_mode = lowercase(strip(opts["phase-mode"])) + phase_mode in ("coherent", "random", "jittered") || + error("Point --phase-mode must be coherent, random, or jittered, got: $phase_mode") + rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) + if phase_mode == "random" + phases_deg = rand(rng, n_sources) .* 360.0 + elseif phase_mode == "jittered" + phases_deg = phases_deg .+ randn(rng, n_sources) .* (parse(Float64, opts["phase-jitter-rad"]) * 180 / pi) + end + + sources = EmissionSource2D[] + for (idx, (depth_m, lateral_m)) in pairs(coordinates) + push!(sources, PointSource2D( + depth=depth_m, + lateral=lateral_m, + frequency=frequencies_mhz[idx] * 1e6, + amplitude=amplitudes_pa[idx], + phase=phases_deg[idx] * pi / 180, + delay=delays_us[idx] * 1e-6, + num_cycles=num_cycles, + )) + end + return sources, Dict{String, Any}( + "source_model" => "point", + "coordinates_m" => [collect(coord) for coord in coordinates], + "n_coordinate_sources" => n_sources, + "n_emission_sources" => length(sources), + "physical_source_count" => length(sources), + "emission_event_count" => length(sources), + "activity_model" => Dict("activity_mode" => "point_tone_burst"), + "phase_mode" => phase_mode, + "frequencies_hz" => frequencies_mhz .* 1e6, + "amplitudes_pa" => amplitudes_pa, + "phases_rad" => phases_deg .* pi ./ 180, + "delays_s" => delays_us .* 1e-6, + "num_cycles" => num_cycles, + "random_seed" => parse(Int, opts["random-seed"]), + ) +end + +function parse_point_sources_3d(opts) + coordinates = parse_coordinate_triples_mm(opts["sources-mm"], "sources-mm") + n_sources = length(coordinates) + frequencies_mhz = expand_source_values( + parse_float_list(opts["source-frequencies-mhz"]), + n_sources, + parse(Float64, opts["frequency-mhz"]), + ) + amplitudes_pa = expand_source_values( + parse_float_list(opts["source-amplitudes-pa"]), + n_sources, + parse(Float64, opts["amplitude-pa"]), + ) + phases_deg = expand_source_values(parse_float_list(opts["phases-deg"]), n_sources, 0.0) + delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_sources, 0.0) + num_cycles = parse(Int, opts["num-cycles"]) + + phase_mode = lowercase(strip(opts["phase-mode"])) + phase_mode in ("coherent", "random", "jittered") || + error("Point --phase-mode must be coherent, random, or jittered, got: $phase_mode") + rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) + if phase_mode == "random" + phases_deg = rand(rng, n_sources) .* 360.0 + elseif phase_mode == "jittered" + phases_deg = phases_deg .+ randn(rng, n_sources) .* (parse(Float64, opts["phase-jitter-rad"]) * 180 / pi) + end + + sources = EmissionSource3D[] + for (idx, (depth_m, lateral_y_m, lateral_z_m)) in pairs(coordinates) + push!(sources, PointSource3D( + depth=depth_m, + lateral_y=lateral_y_m, + lateral_z=lateral_z_m, + frequency=frequencies_mhz[idx] * 1e6, + amplitude=amplitudes_pa[idx], + phase=phases_deg[idx] * pi / 180, + delay=delays_us[idx] * 1e-6, + num_cycles=num_cycles, + )) + end + return sources, Dict{String, Any}( + "source_model" => "point3d", + "coordinates_m" => [collect(coord) for coord in coordinates], + "n_coordinate_sources" => n_sources, + "n_emission_sources" => length(sources), + "physical_source_count" => length(sources), + "emission_event_count" => length(sources), + "activity_model" => Dict("activity_mode" => "point_tone_burst_3d"), + "phase_mode" => phase_mode, + "frequencies_hz" => frequencies_mhz .* 1e6, + "amplitudes_pa" => amplitudes_pa, + "phases_rad" => phases_deg .* pi ./ 180, + "delays_s" => delays_us .* 1e-6, + "num_cycles" => num_cycles, + "random_seed" => parse(Int, opts["random-seed"]), + ) +end + +centerlines_m_3d(centerlines) = [[[p[1], p[2], p[3]] for p in line] for line in centerlines] + +function parse_squiggle_sources_3d(opts, cfg::PAMConfig3D) + anchors = parse_coordinate_triples_mm(opts["anchors-mm"], "anchors-mm") + f0 = parse(Float64, opts["fundamental-mhz"]) * 1e6 + harmonics = parse_int_list(opts["harmonics"]) + isempty(harmonics) && error("--harmonics must be a non-empty integer list.") + harmonic_amplitudes = parse_float_list(opts["harmonic-amplitudes"]) + length(harmonic_amplitudes) == length(harmonics) || + error("--harmonic-amplitudes must have the same length as --harmonics ($(length(harmonics))).") + + n_anchors = length(anchors) + n_bubbles_per = expand_source_values(parse_float_list(opts["n-bubbles"]), n_anchors, 10.0) + delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_anchors, 0.0) + max_sources_raw = parse(Int, opts["vascular-max-sources-per-anchor"]) + max_sources = max_sources_raw <= 0 ? nothing : max_sources_raw + phase_mode = Symbol(replace(lowercase(strip(opts["phase-mode"])), "-" => "_")) + + sources = EmissionSource3D[] + all_centerlines_m = Any[] + anchors_meta = Dict{String, Any}[] + rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) + half_y = cfg.transverse_dim_y / 2 + half_z = cfg.transverse_dim_z / 2 + + for (idx, anchor) in pairs(anchors) + anchor_sources, anchor_meta = make_squiggle_bubble_sources_3d( + [anchor]; + root_length = parse(Float64, opts["vascular-length-mm"]) * 1e-3, + squiggle_amplitude_y = parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, + squiggle_amplitude_x = parse(Float64, opts["vascular-squiggle-amplitude-x-mm"]) * 1e-3, + squiggle_wavelength = parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, + squiggle_phase_x = parse(Float64, opts["squiggle-phase-x-deg"]) * pi / 180, + squiggle_slope_x = parse(Float64, opts["vascular-squiggle-slope"]), + squiggle_slope_y = 0.0, + source_spacing = parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, + position_jitter = parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, + min_separation = parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, + max_sources_per_anchor = max_sources, + depth_bounds = (0.0, Inf), + lateral_y_bounds = (-half_y, half_y), + lateral_z_bounds = (-half_z, half_z), + fundamental = f0, + amplitude = parse(Float64, opts["amplitude-pa"]), + n_bubbles = n_bubbles_per[idx], + harmonics = harmonics, + harmonic_amplitudes = harmonic_amplitudes, + gate_duration = parse(Float64, opts["gate-us"]) * 1e-6, + taper_ratio = parse(Float64, opts["taper-ratio"]), + delay = delays_us[idx] * 1e-6, + phase_mode = phase_mode, + phase_jitter = parse(Float64, opts["phase-jitter-rad"]), + transducer_depth = -parse(Float64, opts["skull-transducer-distance-mm"]) * 1e-3, + transducer_y = 0.0, + transducer_z = 0.0, + c0 = cfg.c0, + rng = rng, + ) + append!(sources, anchor_sources) + anchor_cls = centerlines_m_3d(anchor_meta[:centerlines]) + append!(all_centerlines_m, anchor_cls) + push!(anchors_meta, Dict( + "anchor_m" => collect(anchor), + "source_count" => length(anchor_sources), + "centerlines_m" => anchor_cls, + )) + end + + return sources, Dict{String, Any}( + "source_model" => "squiggle3d", + "anchor_clusters_m" => [collect(anchor) for anchor in anchors], + "n_anchor_clusters" => length(anchors), + "n_emission_sources" => length(sources), + "physical_source_count" => length(sources), + "emission_event_count" => length(sources), + "activity_model" => Dict("activity_mode" => "random_phase_per_window"), + "phase_mode" => String(phase_mode), + "fundamental_hz" => f0, + "harmonics" => harmonics, + "harmonic_amplitudes" => harmonic_amplitudes, + "gate_duration_s" => parse(Float64, opts["gate-us"]) * 1e-6, + "phase_jitter_rad" => parse(Float64, opts["phase-jitter-rad"]), + "random_seed" => parse(Int, opts["random-seed"]), + "n_bubbles_per_cluster" => n_bubbles_per, + "delays_s" => delays_us .* 1e-6, + "squiggle" => Dict( + "length_m" => parse(Float64, opts["vascular-length-mm"]) * 1e-3, + "squiggle_amplitude_y_m" => parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, + "squiggle_amplitude_x_m" => parse(Float64, opts["vascular-squiggle-amplitude-x-mm"]) * 1e-3, + "squiggle_wavelength_m" => parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, + "squiggle_phase_x_deg" => parse(Float64, opts["squiggle-phase-x-deg"]), + "squiggle_slope" => parse(Float64, opts["vascular-squiggle-slope"]), + "source_spacing_m" => parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, + "position_jitter_m" => parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, + "min_separation_m" => parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, + "max_sources_per_anchor" => max_sources_raw, + "truth_radius_m" => parse(Float64, opts["vascular-radius-mm"]) * 1e-3, + "centerlines_m" => all_centerlines_m, + "anchors" => anchors_meta, + ), + ) +end + +function parse_network_sources_3d(opts, cfg::PAMConfig3D) + centers = parse_coordinate_triples_mm(opts["anchors-mm"], "anchors-mm") + f0 = parse(Float64, opts["fundamental-mhz"]) * 1e6 + harmonics = parse_int_list(opts["harmonics"]) + isempty(harmonics) && error("--harmonics must be a non-empty integer list.") + harmonic_amplitudes = parse_float_list(opts["harmonic-amplitudes"]) + length(harmonic_amplitudes) == length(harmonics) || + error("--harmonic-amplitudes must have the same length as --harmonics ($(length(harmonics))).") + + n_centers = length(centers) + n_bubbles_per = expand_source_values(parse_float_list(opts["n-bubbles"]), n_centers, 1.0) + delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_centers, 0.0) + max_sources_raw = parse(Int, opts["network-max-sources-per-center"]) + max_sources = max_sources_raw <= 0 ? nothing : max_sources_raw + phase_mode = Symbol(replace(lowercase(strip(opts["phase-mode"])), "-" => "_")) + network_radius_m = parse(Float64, opts["network-radius-mm"]) * 1e-3 + axial_radius_m = parse(Float64, opts["network-axial-radius-mm"]) * 1e-3 + lateral_y_radius_m = parse(Float64, opts["network-lateral-y-radius-mm"]) * 1e-3 + lateral_z_radius_m = parse(Float64, opts["network-lateral-z-radius-mm"]) * 1e-3 + ellipsoid_radii_m = network_radius_m > 0 ? + [network_radius_m, network_radius_m, network_radius_m] : + [axial_radius_m, lateral_y_radius_m, lateral_z_radius_m] + density_sigma_m = parse(Float64, opts["network-density-sigma-mm"]) * 1e-3 + density_axial_sigma_m = parse(Float64, opts["network-density-axial-sigma-mm"]) * 1e-3 + density_lateral_y_sigma_m = parse(Float64, opts["network-density-lateral-y-sigma-mm"]) * 1e-3 + density_lateral_z_sigma_m = parse(Float64, opts["network-density-lateral-z-sigma-mm"]) * 1e-3 + density_sigmas_m = density_sigma_m > 0 ? + [density_sigma_m, density_sigma_m, density_sigma_m] : + [density_axial_sigma_m, density_lateral_y_sigma_m, density_lateral_z_sigma_m] + + sources = EmissionSource3D[] + all_centerlines_m = Any[] + centers_meta = Dict{String, Any}[] + rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) + half_y = cfg.transverse_dim_y / 2 + half_z = cfg.transverse_dim_z / 2 + + for (idx, center) in pairs(centers) + center_sources, network_meta = make_network_bubble_sources_3d( + [center]; + sphere_radius = network_radius_m, + axial_radius = axial_radius_m, + lateral_y_radius = lateral_y_radius_m, + lateral_z_radius = lateral_z_radius_m, + root_count = parse(Int, opts["network-root-count"]), + generations = parse(Int, opts["network-generations"]), + branch_length = parse(Float64, opts["network-branch-length-mm"]) * 1e-3, + branch_step = parse(Float64, opts["network-branch-step-mm"]) * 1e-3, + branch_angle = parse(Float64, opts["network-branch-angle-deg"]) * pi / 180, + tortuosity = parse(Float64, opts["network-tortuosity"]), + network_orientation = Symbol(replace(lowercase(strip(opts["network-orientation"])), "-" => "_")), + source_spacing = parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, + density_sigma = density_sigma_m, + density_sigma_depth = density_axial_sigma_m, + density_sigma_y = density_lateral_y_sigma_m, + density_sigma_z = density_lateral_z_sigma_m, + min_separation = parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, + max_sources_per_center = max_sources, + depth_bounds = (0.0, Inf), + lateral_y_bounds = (-half_y, half_y), + lateral_z_bounds = (-half_z, half_z), + fundamental = f0, + amplitude = parse(Float64, opts["amplitude-pa"]), + n_bubbles = n_bubbles_per[idx], + harmonics = harmonics, + harmonic_amplitudes = harmonic_amplitudes, + gate_duration = parse(Float64, opts["gate-us"]) * 1e-6, + taper_ratio = parse(Float64, opts["taper-ratio"]), + delay = delays_us[idx] * 1e-6, + phase_mode = phase_mode, + phase_jitter = parse(Float64, opts["phase-jitter-rad"]), + transducer_depth = -parse(Float64, opts["skull-transducer-distance-mm"]) * 1e-3, + transducer_y = 0.0, + transducer_z = 0.0, + c0 = cfg.c0, + rng = rng, + ) + append!(sources, center_sources) + center_cls = centerlines_m_3d(network_meta[:centerlines]) + append!(all_centerlines_m, center_cls) + push!(centers_meta, Dict( + "center_m" => collect(center), + "source_count" => length(center_sources), + "centerline_count" => length(network_meta[:centerlines]), + "centerlines_m" => center_cls, + )) + end + + return sources, Dict{String, Any}( + "source_model" => "network3d", + "network_centers_m" => [collect(center) for center in centers], + "n_network_centers" => length(centers), + "n_emission_sources" => length(sources), + "physical_source_count" => length(sources), + "emission_event_count" => length(sources), + "activity_model" => Dict("activity_mode" => "random_phase_per_window"), + "phase_mode" => String(phase_mode), + "fundamental_hz" => f0, + "harmonics" => harmonics, + "harmonic_amplitudes" => harmonic_amplitudes, + "gate_duration_s" => parse(Float64, opts["gate-us"]) * 1e-6, + "phase_jitter_rad" => parse(Float64, opts["phase-jitter-rad"]), + "random_seed" => parse(Int, opts["random-seed"]), + "n_bubbles_per_cluster" => n_bubbles_per, + "delays_s" => delays_us .* 1e-6, + "network" => Dict( + "radius_m" => network_radius_m, + "axial_radius_m" => axial_radius_m, + "lateral_y_radius_m" => lateral_y_radius_m, + "lateral_z_radius_m" => lateral_z_radius_m, + "ellipsoid_radii_m" => ellipsoid_radii_m, + "root_count" => parse(Int, opts["network-root-count"]), + "generations" => parse(Int, opts["network-generations"]), + "branch_length_m" => parse(Float64, opts["network-branch-length-mm"]) * 1e-3, + "branch_step_m" => parse(Float64, opts["network-branch-step-mm"]) * 1e-3, + "branch_angle_deg" => parse(Float64, opts["network-branch-angle-deg"]), + "tortuosity" => parse(Float64, opts["network-tortuosity"]), + "orientation" => opts["network-orientation"], + "density_sigma_m" => density_sigma_m, + "density_sigmas_m" => density_sigmas_m, + "source_spacing_m" => parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, + "min_separation_m" => parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, + "max_sources_per_center" => max_sources_raw, + "truth_radius_m" => parse(Float64, opts["vascular-radius-mm"]) * 1e-3, + "centerlines_m" => all_centerlines_m, + "centers" => centers_meta, + ), + ) +end + +function parse_squiggle_sources(opts, cfg::PAMConfig) + anchors = parse_coordinate_pairs_mm(opts["anchors-mm"], "anchors-mm") + f0 = parse(Float64, opts["fundamental-mhz"]) * 1e6 + harmonics = parse_int_list(opts["harmonics"]) + isempty(harmonics) && error("--harmonics must be a non-empty integer list.") + harmonic_amplitudes = parse_float_list(opts["harmonic-amplitudes"]) + length(harmonic_amplitudes) == length(harmonics) || + error("--harmonic-amplitudes must have the same length as --harmonics ($(length(harmonics))).") + + n_anchors = length(anchors) + n_bubbles_per = expand_source_values(parse_float_list(opts["n-bubbles"]), n_anchors, 10.0) + delays_us = expand_source_values(parse_float_list(opts["delays-us"]), n_anchors, 0.0) + tx_depth, tx_lateral = parse_transducer_mm(opts["transducer-mm"]) + max_sources_raw = parse(Int, opts["vascular-max-sources-per-anchor"]) + max_sources = max_sources_raw <= 0 ? nothing : max_sources_raw + phase_mode = Symbol(replace(lowercase(strip(opts["phase-mode"])), "-" => "_")) + + sources = EmissionSource2D[] + all_centerlines_m = Any[] + anchors_meta = Dict{String, Any}[] + rng = Random.MersenneTwister(parse(Int, opts["random-seed"])) + for (idx, anchor) in pairs(anchors) + anchor_sources, anchor_meta = make_squiggle_bubble_sources( + [anchor]; + root_length=parse(Float64, opts["vascular-length-mm"]) * 1e-3, + squiggle_amplitude=parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, + squiggle_wavelength=parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, + squiggle_slope=parse(Float64, opts["vascular-squiggle-slope"]), + source_spacing=parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, + position_jitter=parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, + min_separation=parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, + max_sources_per_anchor=max_sources, + depth_bounds=(0.0, Inf), + lateral_bounds=(-cfg.transverse_dim / 2, cfg.transverse_dim / 2), + fundamental=f0, + amplitude=parse(Float64, opts["amplitude-pa"]), + n_bubbles=n_bubbles_per[idx], + harmonics=harmonics, + harmonic_amplitudes=harmonic_amplitudes, + cavitation_model=parse_cavitation_model(opts["cavitation-model"]), + gate_duration=parse(Float64, opts["gate-us"]) * 1e-6, + taper_ratio=parse(Float64, opts["taper-ratio"]), + delay=delays_us[idx] * 1e-6, + phase_mode=phase_mode, + phase_jitter=parse(Float64, opts["phase-jitter-rad"]), + transducer_depth=tx_depth, + transducer_lateral=tx_lateral, + c0=cfg.c0, + rng=rng, + ) + append!(sources, anchor_sources) + anchor_centerlines = centerlines_m(anchor_meta[:centerlines]) + append!(all_centerlines_m, anchor_centerlines) + push!(anchors_meta, Dict( + "anchor_m" => collect(anchor), + "source_count" => length(anchor_sources), + "centerlines_m" => anchor_centerlines, + )) + end + + return sources, Dict{String, Any}( + "source_model" => "squiggle", + "anchor_clusters_m" => [collect(anchor) for anchor in anchors], + "n_anchor_clusters" => length(anchors), + "n_emission_sources" => length(sources), + "physical_source_count" => length(sources), + "emission_event_count" => length(sources), + "activity_model" => Dict("activity_mode" => "random_phase_per_window"), + "phase_mode" => String(phase_mode), + "fundamental_hz" => f0, + "harmonics" => harmonics, + "harmonic_amplitudes" => harmonic_amplitudes, + "cavitation_model" => opts["cavitation-model"], + "gate_duration_s" => parse(Float64, opts["gate-us"]) * 1e-6, + "transducer_m" => [tx_depth, tx_lateral], + "phase_jitter_rad" => parse(Float64, opts["phase-jitter-rad"]), + "random_seed" => parse(Int, opts["random-seed"]), + "n_bubbles_per_cluster" => n_bubbles_per, + "delays_s" => delays_us .* 1e-6, + "squiggle" => Dict( + "length_m" => parse(Float64, opts["vascular-length-mm"]) * 1e-3, + "squiggle_amplitude_m" => parse(Float64, opts["vascular-squiggle-amplitude-mm"]) * 1e-3, + "squiggle_wavelength_m" => parse(Float64, opts["vascular-squiggle-wavelength-mm"]) * 1e-3, + "squiggle_slope" => parse(Float64, opts["vascular-squiggle-slope"]), + "source_spacing_m" => parse(Float64, opts["vascular-source-spacing-mm"]) * 1e-3, + "position_jitter_m" => parse(Float64, opts["vascular-position-jitter-mm"]) * 1e-3, + "min_separation_m" => parse(Float64, opts["vascular-min-separation-mm"]) * 1e-3, + "max_sources_per_anchor" => max_sources_raw, + "truth_radius_m" => parse(Float64, opts["vascular-radius-mm"]) * 1e-3, + "centerlines_m" => all_centerlines_m, + "anchors" => anchors_meta, + ), + ) +end + +function parse_sources(opts, cfg::PAMConfig) + source_model = parse_source_model(opts["source-model"]) + source_model == :point && return parse_point_sources(opts) + source_model == :squiggle && return parse_squiggle_sources(opts, cfg) + error("2D PAM CLI supports --source-model=point or --source-model=squiggle.") +end + diff --git a/test/runtests.jl b/test/runtests.jl index 204c9ab..9fbea4f 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -457,6 +457,48 @@ end @test intensity[4, 1, 1] ≈ 3.0^1.5 end +@testset "PAM 3D detection metrics" begin + cfg = PAMConfig3D( + dx=1e-3, + dy=1e-3, + dz=1e-3, + axial_dim=0.012, + transverse_dim_y=0.012, + transverse_dim_z=0.012, + success_tolerance=0.75e-3, + ) + grid = pam_grid_3d(cfg) + source = PointSource3D(depth=0.004, lateral_y=0.0, lateral_z=0.0, frequency=1e6) + truth_mask = pam_truth_mask_3d([source], grid, cfg; radius=cfg.success_tolerance) + intensity = zeros(Float64, pam_Nx(cfg), pam_Ny(cfg), pam_Nz(cfg)) + truth_idx = source_grid_index_3d(source, cfg) + intensity[truth_idx...] = 1.0 + intensity[end - 1, 2, 2] = 0.8 + + stats = threshold_detection_stats_3d( + intensity, + grid, + cfg, + [source]; + threshold_ratios=[0.5, 0.9], + truth_radius=cfg.success_tolerance, + truth_mask=truth_mask, + ) + + @test length(stats) == 2 + @test stats[1][:predicted_voxels] == 2 + @test stats[1][:precision] ≈ 0.5 + @test stats[1][:source_recall] ≈ 1.0 + @test stats[1][:source_f1] ≈ 2 * 0.5 / 1.5 + @test stats[2][:predicted_voxels] == 1 + @test stats[2][:precision] ≈ 1.0 + @test best_threshold_entry_3d(stats)[:threshold_ratio] == 0.9 + + outlines = threshold_outline_entries_3d(stats) + @test first(outlines).kind == :best_f1 + @test first(outlines).entry[:threshold_ratio] == 0.9 +end + @testset "PAM analysis metrics" begin cfg = PAMConfig( dx=0.5e-3, diff --git a/visualisation/README.md b/visualisation/README.md index 7595d0c..65d86cb 100644 --- a/visualisation/README.md +++ b/visualisation/README.md @@ -16,9 +16,10 @@ Default case: - 3D network source at `45:0:0 mm` - CT skull aberrator, `slice-index=250`, skull distance `20 mm` - `dx=0.2 mm`, `dy=0.2 mm`, `dz=0.2 mm` -- `t_max=400 us` +- `t_max=300 us` - `40 us` windows, `20 us` hop - `40 kHz` reconstruction bandwidth +- random source phases resampled per reconstruction window - GPU k-Wave and GPU reconstruction The default run is intentionally heavy. A quick water smoke test is: @@ -43,8 +44,8 @@ visualisation/outputs/_window_convergence/ The folder contains: -- `data.jld2`: final cumulative volume, truth mask, threshold search results, - selected windows, and per-frame metrics +- `data.jld2`: RF data, medium arrays, final cumulative volume, truth mask, + threshold search results, selected windows, and per-frame metrics - `summary.json`: human-readable run summary - `frames/frame_0001.png`, etc. - `pam_window_convergence.mp4` @@ -72,10 +73,22 @@ Useful options: ```powershell julia --project=. visualisation/make_window_convergence.jl ` --out-dir=visualisation/outputs/test_run ` - --t-max-us=400 ` + --t-max-us=300 ` --dy-mm=0.2 ` --dz-mm=0.2 ` --max-windows=0 ` --fps=12 ` --frames-only=false ``` + +To reuse an existing k-Wave simulation and medium cache: + +```powershell +julia --project=. visualisation/make_window_convergence.jl ` + --from-data=visualisation/outputs/_window_convergence/data.jld2 ` + --out-dir=visualisation/outputs/rerender_attempt +``` + +`--from-data` skips medium construction and k-Wave RF simulation. It still +reruns the window reconstructions so you can adjust rendering and threshold +logic without paying the forward-simulation cost again. diff --git a/visualisation/make_window_convergence.jl b/visualisation/make_window_convergence.jl index f992ada..10259dc 100644 --- a/visualisation/make_window_convergence.jl +++ b/visualisation/make_window_convergence.jl @@ -22,7 +22,7 @@ function parse_cli(args) "out-dir" => "", "random-seed" => "42", "aberrator" => "skull", - "t-max-us" => "400", + "t-max-us" => "300", "dy-mm" => "0.2", "dz-mm" => "0.2", "max-windows" => "0", @@ -33,6 +33,7 @@ function parse_cli(args) "kwave-use-gpu" => "true", "recon-use-gpu" => "true", "zero-pad-factor" => "2", + "from-data" => "", ) for arg in args startswith(arg, "--") || error("Unsupported argument format: $arg") @@ -127,10 +128,17 @@ function make_demo_sources(cfg::PAMConfig3D, seed::Integer) harmonic_amplitudes = [1.0, 0.6, 0.3], gate_duration = 50e-6, taper_ratio = 0.25, - phase_mode = :geometric, + # The actual simulated events are expanded below with fresh random + # phases per reconstruction window. Keep the template sources neutral + # so the saved metadata does not imply geometric phase driving. + phase_mode = :random, transducer_depth = -30e-3, rng = rng, ) + meta[:activity_model] = Dict( + "activity_mode" => "random_phase_per_window", + "template_phase_mode" => "random", + ) return sources, meta end @@ -216,20 +224,17 @@ end function best_final_threshold(final_intensity, truth_mask, grid, cfg, sources; truth_radius::Real) local_ref = max(maximum(Float64.(final_intensity)), eps(Float64)) thresholds = collect(0.10:0.01:0.95) - entries = Dict{Symbol, Any}[] - for ratio in thresholds - cutoff = Float64(ratio) * local_ref - entry = fixed_threshold_stats_3d(final_intensity, cutoff, truth_mask, grid, cfg, sources; truth_radius=truth_radius) - entry[:threshold_ratio] = Float64(ratio) - entry[:absolute_cutoff] = cutoff - push!(entries, entry) - end - best = first(entries) - for entry in entries[2:end] - score = (Float64(entry[:source_f1]), Float64(entry[:precision]), Float64(entry[:threshold_ratio])) - best_score = (Float64(best[:source_f1]), Float64(best[:precision]), Float64(best[:threshold_ratio])) - score > best_score && (best = entry) - end + entries = threshold_detection_stats_3d( + final_intensity, + grid, + cfg, + sources; + threshold_ratios=thresholds, + truth_radius=truth_radius, + truth_mask=truth_mask, + ) + best = best_threshold_entry_3d(entries) + best[:absolute_cutoff] = Float64(best[:threshold_ratio]) * local_ref return best, entries end @@ -468,8 +473,24 @@ function render_frame(path, cumulative, current, truth_mask, fixed_cutoff, best_ return path end -function encode_mp4(frames_dir, mp4_path, fps::Integer) +function find_ffmpeg() ffmpeg = Sys.which("ffmpeg") + !isnothing(ffmpeg) && return ffmpeg + if Sys.iswindows() && haskey(ENV, "LOCALAPPDATA") + winget_root = joinpath(ENV["LOCALAPPDATA"], "Microsoft", "WinGet", "Packages") + if isdir(winget_root) + for (root, _, files) in walkdir(winget_root) + if "ffmpeg.exe" in files + return joinpath(root, "ffmpeg.exe") + end + end + end + end + return nothing +end + +function encode_mp4(frames_dir, mp4_path, fps::Integer) + ffmpeg = find_ffmpeg() pattern = joinpath(frames_dir, "frame_%04d.png") if isnothing(ffmpeg) println("ffmpeg not found on PATH. Frames are ready in: $frames_dir") @@ -499,12 +520,33 @@ function print_dry_run(opts, cfg, fitted_cfg, sources, out_dir, window_config) println(" recon freqs MHz : ", join(round.(default_recon_frequencies(sources) ./ 1e6; digits=3), ", ")) println(" CUDA functional : ", CUDA.functional()) println(" k-Wave available : ", kwave_available()) - println(" ffmpeg : ", something(Sys.which("ffmpeg"), "not found")) + println(" ffmpeg : ", something(find_ffmpeg(), "not found")) return nothing end +function load_cached_inputs(path::AbstractString) + d = load(path) + required = ["cfg", "sources", "network_meta", "c", "rho", "medium_info", "rf", "grid", "simulation_info"] + missing = filter(key -> !haskey(d, key), required) + isempty(missing) || error("--from-data is missing required keys: $(join(missing, ", "))") + return ( + cfg = d["cfg"], + sources = d["sources"], + network_meta = d["network_meta"], + c = d["c"], + rho = d["rho"], + medium_info = d["medium_info"], + rf = d["rf"], + grid = d["grid"], + simulation_info = d["simulation_info"], + sim_sources = haskey(d, "sim_sources") ? d["sim_sources"] : EmissionSource3D[], + n_frames = haskey(d, "n_frames") ? d["n_frames"] : missing, + ) +end + function main() opts = parse_cli(ARGS) + from_data = strip(opts["from-data"]) seed = parse(Int, opts["random-seed"]) aberrator = parse_aberrator(opts["aberrator"]) dry_run = parse_bool(opts["dry-run"]) @@ -523,14 +565,6 @@ function main() summary_path = joinpath(out_dir, "summary.json") mp4_path = joinpath(out_dir, "pam_window_convergence.mp4") - cfg_base = make_demo_config(opts) - sources, network_meta = make_demo_sources(cfg_base, seed) - cfg = fit_pam_config_3d( - cfg_base, - sources; - min_bottom_margin=10e-3, - reference_depth=aberrator == :skull ? 20e-3 : nothing, - ) window_config = PAMWindowConfig( enabled=true, window_duration=40e-6, @@ -540,34 +574,68 @@ function main() accumulation=:intensity, ) + cfg_base = make_demo_config(opts) + if isempty(from_data) + sources, network_meta = make_demo_sources(cfg_base, seed) + cfg = fit_pam_config_3d( + cfg_base, + sources; + min_bottom_margin=10e-3, + reference_depth=aberrator == :skull ? 20e-3 : nothing, + ) + else + cached = load_cached_inputs(abspath(from_data)) + cfg = cached.cfg + sources = cached.sources + network_meta = cached.network_meta + end + if dry_run print_dry_run(opts, cfg_base, cfg, sources, out_dir, window_config) + if !isempty(from_data) + println(" from data : ", abspath(from_data)) + end return nothing end mkpath(frames_dir) - println("Building medium...") - c, rho, medium_info = make_pam_medium_3d( - cfg; - aberrator=aberrator, - skull_to_transducer=20e-3, - slice_index_z=250, - ) + if isempty(from_data) + println("Building medium...") + c, rho, medium_info = make_pam_medium_3d( + cfg; + aberrator=aberrator, + skull_to_transducer=20e-3, + slice_index_z=250, + ) - println("Expanding random-phase-per-window source events...") - rng_sim = Random.MersenneTwister(seed + 1) - sim_sources, n_frames = TranscranialFUS._expand_sources_per_window( - sources, - window_config.window_duration, - window_config.hop, - cfg.t_max, - rng_sim; - variability=SourceVariabilityConfig(frequency_jitter_fraction=0.01), - ) + println("Expanding random-phase-per-window source events...") + rng_sim = Random.MersenneTwister(seed + 1) + sim_sources, n_frames = TranscranialFUS._expand_sources_per_window( + sources, + window_config.window_duration, + window_config.hop, + cfg.t_max, + rng_sim; + variability=SourceVariabilityConfig(frequency_jitter_fraction=0.01), + ) - println("Simulating RF data with $(length(sim_sources)) emission events...") - rf, grid, simulation_info = simulate_point_sources_3d(c, rho, sim_sources, cfg; use_gpu=use_gpu_sim) + println("Simulating RF data with $(length(sim_sources)) emission events...") + rf, grid, simulation_info = simulate_point_sources_3d(c, rho, sim_sources, cfg; use_gpu=use_gpu_sim) + println("Saving RF/medium cache to $data_path") + @save data_path cfg sources network_meta c rho medium_info rf grid simulation_info sim_sources n_frames window_config + else + println("Loading cached RF/medium data from $(abspath(from_data))") + cached = load_cached_inputs(abspath(from_data)) + c = cached.c + rho = cached.rho + medium_info = cached.medium_info + rf = cached.rf + grid = cached.grid + simulation_info = cached.simulation_info + sim_sources = cached.sim_sources + n_frames = cached.n_frames + end selected_ranges, selected_energy, skipped_ranges, window_samples, hop_samples, energy_threshold = qualify_windows(rf, cfg, window_config, max_windows) @@ -654,6 +722,7 @@ function main() "mp4_path" => mp4_path, "random_seed" => seed, "aberrator" => String(aberrator), + "from_data" => isempty(from_data) ? nothing : abspath(from_data), "grid" => Dict( "nx" => pam_Nx(cfg), "ny" => pam_Ny(cfg), @@ -666,6 +735,7 @@ function main() "zero_pad_factor" => cfg.zero_pad_factor, ), "source_model" => "network3d", + "source_phase_mode" => "random_phase_per_window", "source_count" => length(sources), "emission_event_count" => length(sim_sources), "n_frames_from_source_expansion" => n_frames, @@ -699,7 +769,7 @@ function main() println("Saving data bundle...") selected_ranges_pairs = [[first(r), last(r)] for r in selected_ranges] skipped_ranges_pairs = [[first(r), last(r)] for r in skipped_ranges] - @save data_path cfg sources network_meta medium_info simulation_info recon_frequencies bandwidth_hz truth_radius truth_mask final_cumulative best_threshold threshold_entries selected_ranges_pairs skipped_ranges_pairs metrics_by_frame + @save data_path cfg sources network_meta c rho medium_info rf grid simulation_info sim_sources n_frames window_config recon_frequencies bandwidth_hz truth_radius truth_mask final_cumulative best_threshold threshold_entries selected_ranges_pairs skipped_ranges_pairs metrics_by_frame open(summary_path, "w") do io JSON3.pretty(io, summary) From 3035976c0c9d23927e7de4a0b9996a03153b8e99 Mon Sep 17 00:00:00 2001 From: Valentin Magis Date: Sat, 9 May 2026 20:18:42 +0200 Subject: [PATCH 08/19] a million benchmarks and visualisations --- Manifest.toml | 146 ++++++++- Project.toml | 8 +- validation/3D_PAM_Accuracy/plot_results.jl | 198 ++++++------ validation/3D_PAM_Accuracy/results.md | 21 +- .../results_20260509_184401_accuracy3d.png | Bin 0 -> 416948 bytes validation/3D_Scalability/run_scalability.jl | 63 +++- validation/3D_Speed_Benchmark/README.md | 11 + ...esults_20260509_190248_speed_benchmark.pdf | Bin 0 -> 1575527 bytes visualisation/make_window_convergence.jl | 306 +++++++++++------- visualisation/napari/README.md | 52 +++ visualisation/napari/export_for_napari.jl | 103 ++++++ visualisation/napari/show_convergence.py | 303 +++++++++++++++++ 12 files changed, 979 insertions(+), 232 deletions(-) create mode 100644 validation/3D_PAM_Accuracy/results_20260509_184401_accuracy3d.png create mode 100644 validation/3D_Speed_Benchmark/README.md create mode 100644 validation/3D_Speed_Benchmark/results_20260509_190248_speed_benchmark.pdf create mode 100644 visualisation/napari/README.md create mode 100644 visualisation/napari/export_for_napari.jl create mode 100644 visualisation/napari/show_convergence.py diff --git a/Manifest.toml b/Manifest.toml index fc396c6..af2ca54 100644 --- a/Manifest.toml +++ b/Manifest.toml @@ -2,7 +2,7 @@ julia_version = "1.12.6" manifest_format = "2.0" -project_hash = "843780e8d2ff49e8cdec16a219ae2d90dc8d5ac0" +project_hash = "00244827d5ea9d4acca804f08b2c3fbcb7e954d0" [[deps.AbstractFFTs]] deps = ["LinearAlgebra"] @@ -601,6 +601,24 @@ git-tree-sha1 = "53bb909d1151e57e2484c3d1b53e19552b887fb2" uuid = "42e2da0e-8278-4e71-bc24-59509adca0fe" version = "1.0.2" +[[deps.HDF5]] +deps = ["Compat", "HDF5_jll", "Libdl", "MPIPreferences", "Mmap", "Preferences", "Printf", "Random", "Requires", "UUIDs"] +git-tree-sha1 = "491ea627ac824619f34168e29a0427a9e00e3e40" +uuid = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f" +version = "0.17.3" + + [deps.HDF5.extensions] + MPIExt = "MPI" + + [deps.HDF5.weakdeps] + MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195" + +[[deps.HDF5_jll]] +deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LibCURL_jll", "Libdl", "MPIABI_jll", "MPICH_jll", "MPIPreferences", "MPItrampoline_jll", "MicrosoftMPI_jll", "OpenMPI_jll", "OpenSSL_jll", "TOML", "Zlib_jll", "aws_c_s3_jll", "dlfcn_win32_jll", "libaec_jll", "mpif_jll"] +git-tree-sha1 = "45337643a2d97262d5fe72ce1f13e8a662d13d62" +uuid = "0234f1f7-429e-5d53-9886-15a909be8d59" +version = "2.1.2+0" + [[deps.HarfBuzz_jll]] deps = ["Artifacts", "Cairo_jll", "Fontconfig_jll", "FreeType2_jll", "Glib_jll", "Graphite2_jll", "JLLWrappers", "Libdl", "Libffi_jll"] git-tree-sha1 = "f923f9a774fcf3f5cb761bfa43aeadd689714813" @@ -612,6 +630,12 @@ git-tree-sha1 = "2eaa69a7cab70a52b9687c8bf950a5a93ec895ae" uuid = "076d061b-32b6-4027-95e0-9a2c6f6d7e74" version = "0.2.0" +[[deps.Hwloc_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "XML2_jll", "Xorg_libpciaccess_jll"] +git-tree-sha1 = "baaaebd42ed9ee1bd9173cfd56910e55a8622ee1" +uuid = "e33a78d0-f292-5ffc-b300-72abe9b543c8" +version = "2.13.0+1" + [[deps.HypergeometricFunctions]] deps = ["LinearAlgebra", "OpenLibm_jll", "SpecialFunctions"] git-tree-sha1 = "68c173f4f449de5b438ee67ed0c9c748dc31a2ec" @@ -1007,6 +1031,30 @@ git-tree-sha1 = "282cadc186e7b2ae0eeadbd7a4dffed4196ae2aa" uuid = "856f044c-d86e-5d09-b602-aeab76dc8ba7" version = "2025.2.0+0" +[[deps.MPIABI_jll]] +deps = ["Artifacts", "Hwloc_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"] +git-tree-sha1 = "9be143b6045719e8fb019d2b3bc2aebad1184fef" +uuid = "b5ada748-db0f-5fc0-8972-9331c762740c" +version = "0.1.5+0" + +[[deps.MPICH_jll]] +deps = ["Artifacts", "CompilerSupportLibraries_jll", "Hwloc_jll", "JLLWrappers", "Libdl", "MPIPreferences", "TOML"] +git-tree-sha1 = "07dbec8aab01696edc0151a401a6cdfe95b9b885" +uuid = "7cb0a576-ebde-5e09-9194-50597f1243b4" +version = "5.0.1+0" + +[[deps.MPIPreferences]] +deps = ["Libdl", "Preferences"] +git-tree-sha1 = "8e98d5d80b87403c311fd51e8455d4546ba7a5f8" +uuid = "3da0fdf6-3ccc-4f1b-acd9-58baa6c99267" +version = "0.1.12" + +[[deps.MPItrampoline_jll]] +deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML"] +git-tree-sha1 = "675df097f8eeb28998b2cfe3b25655af73d5f7df" +uuid = "f1f71cc9-e9ae-5b93-9b94-4fe0e1ad3748" +version = "5.5.6+0" + [[deps.MacroTools]] git-tree-sha1 = "1e0228a030642014fe5cfe68c2c0a818f9e3f522" uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09" @@ -1046,6 +1094,12 @@ git-tree-sha1 = "535656ce55266bfed0575cd051acc4f36dc869a0" uuid = "0b3b1443-0f03-428d-bdfb-f27f9c1191ea" version = "0.1.15" +[[deps.MicrosoftMPI_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] +git-tree-sha1 = "bc95bf4149bf535c09602e3acdf950d9b4376227" +uuid = "9237b28f-5490-5468-be7b-bb81f5f5e6cf" +version = "10.1.4+3" + [[deps.Missings]] deps = ["DataAPI"] git-tree-sha1 = "ec4f7fbeab05d7747bdf98eb74d130a2a2ed298d" @@ -1151,6 +1205,12 @@ deps = ["Artifacts", "Libdl"] uuid = "05823500-19ac-5b8b-9628-191a04bc5112" version = "0.8.7+0" +[[deps.OpenMPI_jll]] +deps = ["Artifacts", "CompilerSupportLibraries_jll", "Hwloc_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIPreferences", "TOML", "Zlib_jll"] +git-tree-sha1 = "6d6c0ca4824268c1a7dca1f4721c535ac63d9074" +uuid = "fe0851c0-eecd-5654-98d4-656369965a5c" +version = "5.0.11+0" + [[deps.OpenSSL_jll]] deps = ["Artifacts", "Libdl"] uuid = "458c3c95-2e84-50aa-8efc-19380b2a3a95" @@ -1722,6 +1782,12 @@ git-tree-sha1 = "248a7031b3da79a127f14e5dc5f417e26f9f6db7" uuid = "efce3f68-66dc-5838-9240-27a6d6f5f9b6" version = "1.1.0" +[[deps.XML2_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Libiconv_jll", "Zlib_jll"] +git-tree-sha1 = "80d3930c6347cfce7ccf96bd3bafdf079d9c0390" +uuid = "02c8fc9c-b97f-50b9-bbe4-9be30ff0a78a" +version = "2.13.9+0" + [[deps.XZ_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] git-tree-sha1 = "9cce64c0fdd1960b597ba7ecda2950b5ed957438" @@ -1793,18 +1859,84 @@ git-tree-sha1 = "446b23e73536f84e8037f5dce465e92275f6a308" uuid = "3161d3a3-bdf6-5164-811a-617609db77b4" version = "1.5.7+1" +[[deps.aws_c_auth_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_cal_jll", "aws_c_http_jll", "aws_c_sdkutils_jll"] +git-tree-sha1 = "8cab83c96af80a1be968251ce1a0548a7545484d" +uuid = "2b3700d1-4306-52e2-a478-c162f0c514be" +version = "0.9.6+0" + +[[deps.aws_c_cal_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_common_jll"] +git-tree-sha1 = "22c0f42f4a1f0dc5dcfa8fd267c4ac407c455e7a" +uuid = "70f11efc-bab2-57f1-b0f3-22aad4e67c4b" +version = "0.9.13+0" + +[[deps.aws_c_common_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "a759cb9bf456ad792cc7898a81ae333cce9ef02a" +uuid = "73048d1d-b8c4-5092-a58d-866c5e8d1e50" +version = "0.12.6+0" + +[[deps.aws_c_compression_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_common_jll"] +git-tree-sha1 = "7910c72f45f44afd297c39fe43b99c56d5ed22ec" +uuid = "73a04cd5-f3d7-5bac-9290-e8adb709f224" +version = "0.3.2+0" + +[[deps.aws_c_http_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_compression_jll", "aws_c_io_jll"] +git-tree-sha1 = "e358d5a001ef7afbd4f8c5225322512819cda2f2" +uuid = "3254fc65-9028-534d-aa9d-d76d128babc6" +version = "0.10.13+0" + +[[deps.aws_c_io_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_cal_jll", "aws_c_common_jll", "s2n_tls_jll"] +git-tree-sha1 = "7e481d474b2087ee8bbf55b81bf9119f21e396d9" +uuid = "13c41daa-f319-5298-b5eb-5754e0170d52" +version = "0.26.3+0" + +[[deps.aws_c_s3_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_auth_jll", "aws_c_common_jll", "aws_c_http_jll", "aws_checksums_jll", "s2n_tls_jll"] +git-tree-sha1 = "3e9917ab25114feba657e71be41cad068b9f6595" +uuid = "bd1f34fb-993f-5903-a121-aaf302eed6d4" +version = "0.11.5+0" + +[[deps.aws_c_sdkutils_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_common_jll"] +git-tree-sha1 = "c43dfba2c1ab9ea9f02f2c80e86fa16f6460244e" +uuid = "1282aa60-004d-510b-9f52-12498d409daa" +version = "0.2.4+1" + +[[deps.aws_checksums_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "aws_c_common_jll"] +git-tree-sha1 = "2570c8e23f4771a087b12a47edcaaa670ac05a01" +uuid = "b2a88e68-78e7-5e94-8c20-c02986ec140e" +version = "0.2.10+0" + [[deps.demumble_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] git-tree-sha1 = "6498e3581023f8e530f34760d18f75a69e3a4ea8" uuid = "1e29f10c-031c-5a83-9565-69cddfc27673" version = "1.3.0+0" +[[deps.dlfcn_win32_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "e141d67ffe550eadfb5af1bdbdaf138031e4805f" +uuid = "c4b69c83-5512-53e3-94e6-de98773c479f" +version = "1.4.2+0" + [[deps.isoband_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] git-tree-sha1 = "51b5eeb3f98367157a7a12a1fb0aa5328946c03c" uuid = "9a68df92-36a6-505f-a73e-abb412b6bfb4" version = "0.2.3+0" +[[deps.libaec_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "1411bc34c180946d3cef591de1384012afa6edee" +uuid = "477f73a3-ac25-53e9-8cc3-50b2fa2566f0" +version = "1.1.6+0" + [[deps.libaom_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] git-tree-sha1 = "371cc681c00a3ccc3fbc5c0fb91f58ba9bec1ecf" @@ -1870,6 +2002,12 @@ git-tree-sha1 = "717df6f6892af4ee13279a73aa58474e58a88667" uuid = "f8abcde7-e9b7-5caa-b8af-a437887ae8e4" version = "2.3.1+0" +[[deps.mpif_jll]] +deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "MPIABI_jll", "MPICH_jll", "MPIPreferences", "MPItrampoline_jll", "MicrosoftMPI_jll", "OpenMPI_jll", "TOML"] +git-tree-sha1 = "a8083ee0737c243c8f40a4ba86a0956997facb73" +uuid = "9aeb927a-4695-514f-a259-621a69f20ec0" +version = "0.1.7+0" + [[deps.nghttp2_jll]] deps = ["Artifacts", "Libdl"] uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d" @@ -1892,6 +2030,12 @@ git-tree-sha1 = "f349584316617063160a947a82638f7611a8ef0f" uuid = "4d7b5844-a134-5dcd-ac86-c8f19cd51bed" version = "0.41.3+0" +[[deps.s2n_tls_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl"] +git-tree-sha1 = "64ae051c6f03044eb7d98027d1b552b4e21e650c" +uuid = "cddc5d3d-934d-5d3a-9747-62fc12ea3f48" +version = "1.7.3+0" + [[deps.x264_jll]] deps = ["Artifacts", "JLLWrappers", "Libdl"] git-tree-sha1 = "14cc7083fc6dff3cc44f2bc435ee96d06ed79aa7" diff --git a/Project.toml b/Project.toml index 582fdbf..e64ec11 100644 --- a/Project.toml +++ b/Project.toml @@ -1,14 +1,15 @@ name = "TranscranialFUS" uuid = "a2de8f33-df8e-4198-bbcc-8a183cd2f9f0" -authors = ["Valentin Magis, Codex, Claude"] version = "0.1.0" +authors = ["Valentin Magis, Codex, Claude"] [deps] +CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" CondaPkg = "992eb4ea-22a4-4c89-a5bb-47a3300528ab" -CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" DICOM = "a26e6606-dd52-5f6a-a97f-4f611373d757" FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341" +HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f" Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59" JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819" JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1" @@ -17,11 +18,12 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" [compat] +CUDA = "5" CairoMakie = "0.15" CondaPkg = "0.2" -CUDA = "5" DICOM = "0.11" FFTW = "1" +HDF5 = "0.17.3" Interpolations = "0.16" JLD2 = "0.6" JSON3 = "1" diff --git a/validation/3D_PAM_Accuracy/plot_results.jl b/validation/3D_PAM_Accuracy/plot_results.jl index 23980e9..b7872c7 100644 --- a/validation/3D_PAM_Accuracy/plot_results.jl +++ b/validation/3D_PAM_Accuracy/plot_results.jl @@ -1,11 +1,17 @@ """ Plot 3D PAM localization accuracy from saved validation results. -Produces a two-panel Axis3 figure: left = geometric ASA, right = HASA. -Each of the 27 sources is shown as a scatter point at its true 3D position. -Dot colour and size encode the radial localization error. -The skull cross-section (y-z plane at x = SKULL_DIST) is overlaid as a -semi-transparent heatmap slice for spatial context. +Layout matches Fig. 2 in the paper: + • Receiver aperture outline at the TOP (depth = 0) + • Source error bubbles below, sized by radial localisation error + • Dashed stem lines from each source up to skull depth as reference + +Coordinate mapping: + Plot X = lateral Y (simulation), Plot Y = lateral Z (simulation), + Plot Z = –depth → receiver at Z = 0 (top), deep sources at Z ≈ –60 (bottom). + Z tick labels are shown as positive depth values in mm. + +Saved as PNG (not PDF) to avoid 800+ MB vector output. Usage: julia --project=. validation/3D_PAM_Accuracy/plot_results.jl [results_file.jld2] @@ -14,7 +20,7 @@ Usage: using Pkg Pkg.activate(joinpath(@__DIR__, "..", "..")) -using CairoMakie, JLD2, TranscranialFUS, Statistics, Printf +using CairoMakie, JLD2, Statistics, Printf # ── Load results ────────────────────────────────────────────────────────────── @@ -44,7 +50,7 @@ TRANS_DIM = d["TRANS_DIM"] SKULL_DIST = d["SKULL_DIST"] SLICE_INDEX = d["SLICE_INDEX"] -# ── Print summary table ─────────────────────────────────────────────────────── +# ── Print summary ───────────────────────────────────────────────────────────── geo_all = filter(!isnan, geo_errors_mm) hasa_all = filter(!isnan, hasa_errors_mm) @@ -55,117 +61,96 @@ println(" ──────────────┼──────── @printf(" HASA │ %.2f ± %.2f mm (n=%d)\n", mean(hasa_all), std(hasa_all), length(hasa_all)) println() -# ── Rebuild skull medium for background slice ───────────────────────────────── - -sim_cfg = PAMConfig3D( - dx = DX, - dy = DX, - dz = DX, - axial_dim = AXIAL_DIM, - transverse_dim_y = TRANS_DIM, - transverse_dim_z = TRANS_DIM, - dt = DT, - t_max = T_MAX, - receiver_aperture_y = APERTURE_MM * 1e-3, - receiver_aperture_z = APERTURE_MM * 1e-3, -) -println("Rebuilding skull medium for background slice…") -c, _, _ = make_pam_medium_3d( - sim_cfg; - aberrator = :skull, - skull_to_transducer = SKULL_DIST, - slice_index_z = SLICE_INDEX, -) - -# ── Coordinate arrays ───────────────────────────────────────────────────────── +# ── Coordinate mapping ──────────────────────────────────────────────────────── +# +# Plot axis → simulation quantity +# X = lateral Y (horizontal left–right) +# Y = lateral Z (horizontal front–back) +# Z = –depth (vertical: 0 = receiver plane at top, negative = deeper) +# +# This puts the receiver plate on top, sources below — matching Fig. 2 geometry. -rr = receiver_row(sim_cfg) -dx_mm = DX * 1e3 -Ny = pam_Ny(sim_cfg) -Nz = pam_Nz(sim_cfg) -ax_coords = [(i - rr) * dx_mm for i in 1:pam_Nx(sim_cfg)] -y_coords = [(j - (Ny ÷ 2 + 1)) * dx_mm for j in 1:Ny] -z_coords = [(k - (Nz ÷ 2 + 1)) * dx_mm for k in 1:Nz] - -# Skull cross-section at the outer skull face depth -skull_depth_mm = SKULL_DIST * 1e3 -skull_row_idx = argmin(abs.(ax_coords .- skull_depth_mm)) -skull_slice_c = c[skull_row_idx, :, :] # (Ny, Nz) sound-speed map +skull_plot_z = -SKULL_DIST * 1e3 # e.g. –20 mm (used as stem reference) # ── Error → visual encoding ─────────────────────────────────────────────────── -MAX_ERR = 6.0 -MIN_MS = 6.0 -MAX_MS = 24.0 -errcmap = :plasma +MAX_ERR = 6.0 +MIN_MS = 8.0 +MAX_MS = 30.0 +errcmap = :plasma err_to_ms(e) = MIN_MS + (MAX_MS - MIN_MS) * clamp(e, 0.0, MAX_ERR) / MAX_ERR -# ── Figure ──────────────────────────────────────────────────────────────────── +# Z axis ticks: actual values are negative, labels shown as positive depth +max_depth = maximum(AXIAL_MM) +tick_depths = 0.0:10.0:max_depth # positive depth values +ztick_vals = collect(-tick_depths) # e.g. [0, -10, -20, ..., -60] +ztick_labels = [string(Int(d)) for d in tick_depths] -update_theme!(fontsize = 9) +# ── Figure ──────────────────────────────────────────────────────────────────── -fig = Figure(size = (900, 440)) +update_theme!(fontsize = 10) +fig = Figure(size = (1000, 520)) -panels = [ - ("Geometric ASA", geo_errors_mm), - ("HASA", hasa_errors_mm), -] +panels = [("Geometric ASA", geo_errors_mm), ("HASA", hasa_errors_mm)] for (panel_col, (panel_label, errors)) in enumerate(panels) ax = Axis3(fig[1, panel_col]; - xlabel = "Depth [mm]", - ylabel = "Lateral Y [mm]", - zlabel = "Lateral Z [mm]", + xlabel = "Lateral Y [mm]", + ylabel = "Lateral Z [mm]", + zlabel = "Depth [mm]", title = panel_label, aspect = :data, - perspectiveness = 0.3, - azimuth = 5π / 8, - elevation = π / 10, + perspectiveness = 0.35, + azimuth = 5π / 4, # standard isometric-ish: both lateral axes visible + elevation = π / 5, # ~36° top-down so depth separation is clear + zticks = (ztick_vals, ztick_labels), + xlabeloffset = 40, + ylabeloffset = 40, + zlabeloffset = 55, ) - # Semi-transparent skull slice at the skull depth - surface!(ax, - fill(skull_depth_mm, Ny, Nz), - repeat(y_coords, 1, Nz), - repeat(reshape(z_coords, 1, Nz), Ny, 1); - color = Float32.(skull_slice_c), - colormap = :grays, - colorrange = (1400.0f0, 2100.0f0), - alpha = 0.35, - shading = NoShading, - ) - - # Source scatter: collect all 27 points - xs = Float64[]; ys = Float64[]; zs = Float64[] - cs = Float64[]; ms = Float64[] + # Receiver aperture outline at top (Z = 0) + half = APERTURE_MM / 2.0 + apy = [-half, half, half, -half, -half] + apz = [-half, -half, half, half, -half] + lines!(ax, apy, apz, fill(0.0, 5); color = :black, linewidth = 1.4) + + # Collect sources in plot coordinates + xs_plot = Float64[] # lateral Y + ys_plot = Float64[] # lateral Z + zs_plot = Float64[] # -depth + cs = Float64[] + ms = Float64[] for (ai, ax_mm) in enumerate(AXIAL_MM), (yi, ly_mm) in enumerate(LATERAL_Y_MM), (zi, lz_mm) in enumerate(LATERAL_Z_MM) e = errors[ai, yi, zi] isnan(e) && continue - push!(xs, Float64(ax_mm)) - push!(ys, Float64(ly_mm)) - push!(zs, Float64(lz_mm)) + push!(xs_plot, Float64(ly_mm)) + push!(ys_plot, Float64(lz_mm)) + push!(zs_plot, -Float64(ax_mm)) push!(cs, clamp(e, 0.0, MAX_ERR)) push!(ms, err_to_ms(e)) end - scatter!(ax, xs, ys, zs; - color = cs, - colorrange = (0.0, MAX_ERR), - colormap = errcmap, - markersize = ms, - strokewidth = 0.5, - strokecolor = :black, - ) - - # Receiver aperture outline at depth = 0 - half = APERTURE_MM / 2.0 - apts = [(-half, -half), (half, -half), (half, half), (-half, half), (-half, -half)] - apt_ys = [p[1] for p in apts] - apt_zs = [p[2] for p in apts] - lines!(ax, fill(0.0, 5), apt_ys, apt_zs; color = :gray50, linewidth = 0.8) + # Dashed stem lines from each source UP to the skull plane + for (xp, yp, zp) in zip(xs_plot, ys_plot, zs_plot) + lines!(ax, [xp, xp], [yp, yp], [skull_plot_z, zp]; + color = :gray55, linewidth = 0.9, linestyle = :dash) + end + # Cross markers at skull level to anchor the stems + scatter!(ax, xs_plot, ys_plot, fill(skull_plot_z, length(xs_plot)); + marker = :cross, markersize = 7, color = :gray45, strokewidth = 0) + + # Error bubbles (on top of stems) + scatter!(ax, xs_plot, ys_plot, zs_plot; + color = cs, + colorrange = (0.0, MAX_ERR), + colormap = errcmap, + markersize = ms, + strokewidth = 0.8, + strokecolor = :black) end # Shared error colorbar @@ -174,17 +159,34 @@ Colorbar(fig[1, 3]; colorrange = (0.0, MAX_ERR), label = "Radial Error [mm]", width = 14, - ticklabelsize = 8, - labelsize = 9, + ticklabelsize = 9, + labelsize = 10, ticks = 0:1:Int(MAX_ERR), ) -colgap!(fig.layout, 8) +# Bubble size legend +leg_ax = Axis(fig[2, 1:2]; height = 44, aspect = nothing, + xautolimitmargin = (0,0), yautolimitmargin = (0,0)) +hidedecorations!(leg_ax); hidespines!(leg_ax) +for (i, e) in enumerate([0.0, 2.0, 4.0, 6.0]) + scatter!(leg_ax, [i * 70.0], [22.0]; + color = :gray80, markersize = err_to_ms(e), + strokewidth = 0.8, strokecolor = :black) + text!(leg_ax, i * 70.0, 3.0; text = "$(Int(e)) mm", + align = (:center, :bottom), fontsize = 8) +end +text!(leg_ax, 8.0, 22.0; text = "Bubble size = error:", + align = (:left, :center), fontsize = 8) +xlims!(leg_ax, 0, 330); ylims!(leg_ax, 0, 44) + +rowsize!(fig.layout, 2, Fixed(44)) +colgap!(fig.layout, 6) +rowgap!(fig.layout, 4) -# ── Save figure ─────────────────────────────────────────────────────────────── +# ── Save as PNG ─────────────────────────────────────────────────────────────── -figfile = replace(results_file, r"\.jld2$" => "_accuracy3d.pdf") -save(figfile, fig) +figfile = replace(results_file, r"\.jld2$" => "_accuracy3d.png") +save(figfile, fig; px_per_unit = 2) println("Saved → $figfile") # ── Write results.md ────────────────────────────────────────────────────────── diff --git a/validation/3D_PAM_Accuracy/results.md b/validation/3D_PAM_Accuracy/results.md index 0a9df1a..4ba5bee 100644 --- a/validation/3D_PAM_Accuracy/results.md +++ b/validation/3D_PAM_Accuracy/results.md @@ -1,3 +1,22 @@ # 3D PAM Accuracy Validation -*Results not yet generated. Run `run_validation.jl` then `plot_results.jl`.* +**Aperture:** 64 mm × 64 mm +**Sources:** 3 axial × 3 y × 3 z = 27 total +**Frequency:** 1.0 MHz +**Grid:** 200 µm isotropic +**Skull:** CT slice 250, outer surface at 20 mm + +| Method | Mean error | Std error | n | +|---------------|-----------|-----------|---| +| Geometric ASA | 1.77 mm | 0.88 mm | 27 | +| HASA | 0.49 mm | 0.23 mm | 27 | + +## Per-depth breakdown + +| Depth | Geo mean±std | HASA mean±std | +|-------|----------------|----------------| +| 40 mm | 1.51 ± 0.95 mm | 0.68 ± 0.20 mm | +| 50 mm | 1.82 ± 0.90 mm | 0.47 ± 0.13 mm | +| 60 mm | 1.98 ± 0.84 mm | 0.30 ± 0.17 mm | + +*Figure: results_20260509_184401_accuracy3d.png* diff --git a/validation/3D_PAM_Accuracy/results_20260509_184401_accuracy3d.png b/validation/3D_PAM_Accuracy/results_20260509_184401_accuracy3d.png new file mode 100644 index 0000000000000000000000000000000000000000..61b0be5984bf65fe636108a7d152fd40c8de6590 GIT binary patch literal 416948 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"?" : @sprintf("%.0f", eta_s / 60) + Ny_tgt = round(Int, apt_mm * 1e-3 / DX) - @printf("[%2d/%d] depth=%3.0f mm, aperture=%3.0f mm (Ny=Nz=%d, %d march rows) … ", + @printf("[%2d/%d] depth=%3.0f mm, aperture=%3.0f mm (Ny=Nz=%d, %d march rows, ETA ~%s min) … ", s_count, n_total, depth_mm, apt_mm, Ny_tgt, - round(Int, depth_mm * 1e-3 / AXIAL_STEP)) + round(Int, depth_mm * 1e-3 / AXIAL_STEP), eta_str) flush(stdout) # Reconstruction config for this (depth, aperture) @@ -232,8 +266,18 @@ for (di, depth_mm) in enumerate(DEPTHS_MM) end timing_wall_s[di, ai] = t_wall - @printf("%.2f s (march %.2f s)\n", t_wall, timing_march_s[di, ai]) + + # Free CPU temporaries and flush GPU memory pool before the next (larger) run. + rf_apt = nothing + c_recon = nothing + GC.gc(true) + CUDA.reclaim() + + global n_run += 1 + n_done = count(!isnan, timing_wall_s) + save_progress() + @printf(" [progress saved — %d/%d done]\n", n_done, n_total) end end @@ -264,13 +308,6 @@ outdir = @__DIR__ ts = Dates.format(now(), "yyyymmdd_HHMMSS") outfile = joinpath(outdir, "results_$(ts).jld2") -jldsave(outfile; - timing_wall_s, - timing_march_s, - APERTURES_MM, - DEPTHS_MM, - FREQ, NUM_CYCLES, DX, DT, T_MAX, AXIAL_STEP, BANDWIDTH, - SKULL_DIST, SLICE_INDEX, - sim_time_s = t_sim, -) +save_progress() +mv(PROGRESS_FILE, outfile; force=true) println("Results saved → $outfile") diff --git a/validation/3D_Speed_Benchmark/README.md b/validation/3D_Speed_Benchmark/README.md new file mode 100644 index 0000000..cc998be --- /dev/null +++ b/validation/3D_Speed_Benchmark/README.md @@ -0,0 +1,11 @@ +# 3D PAM Speed Benchmark + +Wall-clock reconstruction times for a single centre source at 50 mm depth, +64 mm × 64 mm aperture, 0.2 mm grid, CT skull at 20 mm. + +| | CPU | GPU | +|--------|---------|--------| +| **ASA** | 37.1 s | 34.4 s | +| **HASA** | 46.7 s | 9.7 s | + +HASA massively benefits from GPU speedup. 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