Adds mri.phantom.vial-signal pipeline to analyse phantom data

specs/australian-imaging-service/mri/phantoms/vial-signal.yaml

@@ -0,0 +1,49 @@
+schema_version: '2.0'
+title: Phantom vial signal metrics
+version: &package_version "0.1.7"
+authors:
+  - name: Arkiev D'Souza
+    email: arkiev.dsouza@sydney.edu.au
+  - name: Thomas G. Close
+    email: tom.g.close@gmail.com
+docs:
+  description: >-
+    End-to-end pydra workflow for processing a GSP SPIRIT or 120E phantom MRI
+    session.
+
+    Supports three processing stages:
+
+      Stage 1 — DWI preprocessing: automatic series classification and
+      phase-encoding correction mode selection (rpe_none, rpe_pair, rpe_all,
+      rpe_split), FSL dwifslpreproc, DWI bias correction, tensor fitting to
+      produce ADC and FA maps, and T1-to-DWI coregistration via FLIRT.
+
+      Stage 2 — Phantom QC in DWI space: iterative ANTs rigid registration of
+      the T1 (in DWI space) to the phantom template, inverse transform of vial
+      segmentations into DWI space, and per-vial ADC and FA metric extraction.
+
+      Stage 3 — Native contrast QC: registration of the T1 to the phantom
+      template, inverse transform of vial segmentations, and per-vial metric
+      extraction across all contrast images (T1, IR, TE). Generates
+      publication-quality scatter plots and parametric map plots.
+
+    All stages are invoked from a single command pointing at a DICOM session
+    directory; series classification and preprocessing mode selection are fully
+    automatic.
+  info_url: https://github.com/Australian-Imaging-Service/phantomkit
+packages:
+  pip:
+    phantomkit: *package_version
+    pydra: 1.0a9
+  neurodocker:
+    dcm2niix: v1.0.20240202
+    mrtrix3: 3.0.4
+    ants: 2.6.2
+    fsl: 6.0.7.9
+commands:
+  all_metrics:
+    operates_on: medimage/session
+    task: phantomkit.analyses.vial_signal:VialSignalAnalysis
+  pipeline:
+    operates_on: medimage/session
+    task: phantomkit.pipeline:run_pipeline

tests/test_vial_signal.py

@@ -0,0 +1,99 @@
+import json
+import typing as ty
+from pathlib import Path
+from pydra2app.core.cli import make
+from pydra2app.xnat import XnatApp
+from frametree.core.utils import show_cli_trace
+from pydra2app.xnat.deploy import install_and_launch_xnat_cs_command
+from conftest import upload_test_dataset_to_xnat, test_data_dir
+
+PKG_DIR = Path(__file__).parent.parent
+
+SPEC_PATH = (
+    PKG_DIR
+    / "specs"
+    / "australian-imaging-service"
+    / "mri"
+    / "phantoms"
+    / "vial-signal.yaml"
+)
+
+SKIP_BUILD = False
+
+
+def test_vial_signal_app(
+    run_prefix: str,
+    xnat_connect: ty.Any,
+    cli_runner: ty.Callable[..., ty.Any],
+    tmp_path: Path,
+):
+
+    build_dir = tmp_path / "build"
+
+    build_dir.mkdir(exist_ok=True, parents=True)
+
+    project_id = f"{run_prefix}qualitycontrolgspspirit"
+
+    test_data = test_data_dir / "specs" / "mri" / "phantoms" / "vial-signal"
+    upload_test_dataset_to_xnat(project_id, test_data, xnat_connect)
+
+    if SKIP_BUILD:
+        build_arg = "--generate-only"
+    else:
+        build_arg = "--build"
+
+    result = cli_runner(
+        make,
+        [
+            "xnat",
+            str(SPEC_PATH),
+            "--build-dir",
+            str(build_dir),
+            build_arg,
+            "--for-localhost",
+            "--use-local-packages",
+            "--raise-errors",
+        ],
+    )
+
+    assert result.exit_code == 0, show_cli_trace(result)
+
+    image_spec = XnatApp.load(SPEC_PATH)
+
+    command_inputs = {
+        "all_metrics": {
+            "input_image": "foo_bar",
+        }
+    }
+
+    with xnat_connect() as xlogin:
+
+        for command_obj in image_spec.commands:
+            with open(build_dir / "xnat_commands" / (command_obj.name + ".json")) as f:
+                command_json = json.load(f)
+            command_json["name"] = command_json["label"] = (
+                image_spec.name + command_obj.name + run_prefix
+            )
+
+            test_xsession = next(iter(xlogin.projects[project_id].experiments.values()))
+
+            inputs_json = command_inputs[command_obj.name]
+            inputs_json["pydra2app_flags"] = (
+                "--worker debug "
+                "--work /work "  # NB: work dir moved inside container due to file-locking issue on some mounted volumes (see https://github.com/tox-dev/py-filelock/issues/147)
+                "--dataset-name default "
+                "--logger frametree debug "
+                "--logger frametree-xnat debug "
+                "--logger pydra2app debug "
+                "--logger pydra2app-xnat debug "
+            )
+
+            workflow_id, status, out_str = install_and_launch_xnat_cs_command(
+                command_json=command_json,
+                project_id=project_id,
+                session_id=test_xsession.id,
+                inputs=inputs_json,
+                xlogin=xlogin,
+                timeout=30000,
+            )
+            assert status == "Complete", f"Workflow {workflow_id} failed.\n{out_str}"