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7e57cfa
Update zea to pre-release
tristan-deep May 18, 2026
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small readme changes
tristan-deep May 18, 2026
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PyPi supported pre-release tag
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uv lock
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Merge remote-tracking branch 'upstream/main'
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51d5b6d
update lens correction verasonics
tristan-deep Jun 19, 2026
dfb6cae
update outdated module docstrings
tristan-deep Jun 19, 2026
753cd27
remove redundant conversion
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727b161
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tristan-deep Jun 22, 2026
f892543
Merge branch 'main' of https://github.com/tristan-deep/OpenH-RF
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Merge branch 'main' of https://github.com/tristan-deep/OpenH-RF
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Merge remote-tracking branch 'origin/main'
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a02a276
Add datasets/: reference reconstructions for the published corpus
tristan-deep Sep 17, 2026
31ab797
ruff format
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722c4ba
uv run ruff check --fix
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ad618ad
Pin ruff to 0.16.8 to keep CI and local lint/format in sync
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ffdf5b2
Apply ruff format fixes (comment spacing, blank line)
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b084723
Merge branch 'add-datasets-folder'
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c94958d
Ignore generated figures, except a data card's own assets
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Merge branch 'add-datasets-folder'
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Module_A_readme_update
ZongzeLeo Sep 17, 2026
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Module_C readme update
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Create assets
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Add figure for Module C
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Delete .gitkeep
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559dd2a
add link to image in asset
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224f237
Add example reconstruction image to README
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7036227
Restore pre-force-push main history (ancestry only)
tristan-deep Sep 18, 2026
a2418c1
Add TU/e cardiac README gallery
swpenninga Sep 18, 2026
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Merge pull request #3 from swpenninga/main
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149aff3
Simplify module_A reconstruction scripts
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Merge pull request #5 from tristan-deep/assets/tue-carotid-main-png
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Add assets & update readme
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Merge pull request #6 from Sidaty1/strasbourg-basel-update
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46b459b
update quantitative values in READMEs (checked with data on HF)
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5c1d9ed
Merge pull request #7 from tristan-deep/readme-numeric-claim-fixes
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9554aa5
Adapt the OpenH-RF Resolve submission for GH/HF split
mxncr Sep 18, 2026
eed37a6
Update README with dataset naming convention
ycpan1597 Sep 18, 2026
28c222f
added assets folder and main.png to datasets/vanderbilt
Sep 18, 2026
aeaa504
kaist-snubh-barreleye: add main image asset, update README, default f…
Seokhwan-Oh Sep 19, 2026
c04e395
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waltsims Sep 19, 2026
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Update readme Vanderbilt
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d0955d7
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technion: add assets/ with one main image per dataset
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c4caa5d
vanderbilt: drop redundant static image from README
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technion: add zea process commands, bladder cine gif
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08a5eef
add high res image nvidia
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509fc2b
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539cd07
bladder frame update
tristan-deep Sep 21, 2026
7b4116b
nv-raw2insights-us: select the main.png frame and fix pipeline.yaml
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update tum submission
Felixduelmer Sep 21, 2026
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Felixduelmer Sep 21, 2026
0547df3
Some minor fixes:
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75ada54
address comments and add specific hero image
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tue-cardiac: write the reference render into assets/
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32f9725
Merge pull request #23 from tristan-deep/tue-cardiac-output-to-assets
tristan-deep Sep 21, 2026
36c0eb5
Update Colorado Boulder README
ansa6319 Sep 21, 2026
3766912
Add files via upload
ansa6319 Sep 21, 2026
1f2c105
unc-openpros: drop references to the unshipped convert.py
tristan-deep Sep 21, 2026
2ec2a4a
unc-openpros: add the card frontmatter and the hero image
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53c38e3
Merge pull request #25 from tristan-deep/unc-openpros-drop-convert-py
tristan-deep Sep 22, 2026
40b9f8e
colorado-boulder: lead the card with tracked SSA sweep loops
tristan-deep Sep 22, 2026
59e23e1
remove hardcoded cpu device
tristan-deep Sep 22, 2026
72f34d0
clean up reconstruct.py
tristan-deep Sep 22, 2026
dab91a4
vanderbilt, tumunich: record the published pipeline.yaml path
tristan-deep Sep 22, 2026
d802fa7
Merge pull request #26 from tristan-deep/handled-pipeline-hf-constants
tristan-deep Sep 22, 2026
6b0a5cc
datasets: clean up reconstruct.py across the corpus
tristan-deep Sep 22, 2026
6b0ef28
save to assets folder
tristan-deep Sep 22, 2026
c071514
assets to this file too
tristan-deep Sep 22, 2026
4a5330c
tue-aaa updates
tristan-deep Sep 22, 2026
17e4b4c
politorino update gif
tristan-deep Sep 22, 2026
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update siemens healthineers gif
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90e72fc
tue-aaa assets update
tristan-deep Sep 22, 2026
b9bd5ca
add twente cavitation assets
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twente-vortexflow and waterloo-muscle updates
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tel-aviv add assets
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Merge branch 'main' of github.com:tristan-deep/OpenH-RF into reconstr…
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c666efa
adding main / hero images to concordia, dartmouth-uct and us4us
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siemens datacard update (hero + main images)
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34e9fd0
wpi: fix reconstruct.py default, README inconsistencies, add hero assets
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datasets: restructure every data card to the common README layout
tristan-deep Sep 23, 2026
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Merge remote-tracking branch 'origin/main' into update-readme-structure
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be48da1
WPI reorder sections
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0289a18
datasets: unwrap hard line breaks in every data card
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110ef2b
Merge pull request #28 from tristan-deep/update-readme-structure
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weizmann-sampl: add assets/main.png
tristan-deep Sep 23, 2026
16eec1d
Change SOS_RANGE in reconstcution, update main figure, add comparison…
PengJin95 Sep 23, 2026
d6e8f7c
waterloo-carotid, waterloo-largeartery: refresh hero assets and data …
Sep 24, 2026
b6e9bdc
tue-cardiac: add author middle initials to the citation
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a5cae85
Merge pull request #29 from PengJin95/unc_openpros_doublecheck
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5e2ca30
Merge pull request #31 from tristan-deep/tue-cardiac-author-initials
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unc-openpros: point the caption link at the sample it names
tristan-deep Sep 24, 2026
1dc6909
Merge pull request #32 from tristan-deep/unc-openpros-caption-link
tristan-deep Sep 24, 2026
8040648
oslo: add hero and main images for the collection and each sub-dataset
tristan-deep Sep 24, 2026
b60c4ac
oslo: add a zea process pipeline.yaml per sub-dataset
tristan-deep Sep 24, 2026
1cf0032
unc-liver: add the split CSV, center the hero image
tristan-deep Sep 24, 2026
bf6d72c
add:twente cavitation update
HermendR Sep 24, 2026
a4ac5e3
fix: correctly located files
HermendR Sep 24, 2026
c4dbc1b
Merge pull request #34 from tristan-deep/oslo-hero-main
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4988009
Merge pull request #35 from tristan-deep/unc-liver-card-fixes
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e66a957
Update twente-microbubblesim
AnassH17 Sep 24, 2026
9d1a26e
waterloo-largeartery: rename to waterloo-femoralvein
tristan-deep Sep 24, 2026
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Merge branch 'main' into twente-cavitation-update
HermendR Sep 24, 2026
ed6f51b
Merge remote-tracking branch 'origin/main' into waterloo-datacard-upd…
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523457c
Clarify Twente vortexflow dataset metadata
rienkcz Sep 24, 2026
2aa1d98
Import hdf5plugin; update reference images
rienkcz Sep 24, 2026
5029434
fixed default settings for reconstruct.py
Sep 24, 2026
f330ef2
twente-microbubblesim: standardize reconstruct.py, fold away utils.py
tristan-deep Sep 24, 2026
964cffc
fix pipeline yaml for femvein as well
Sep 24, 2026
34a405d
twente-cavitation: fix reconstruct.py, card links and captions
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Merge pull request #36 from HermendR/twente-cavitation-update
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update image
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waterloo-femoralvein: point Hub paths at waterloo-femoralvein
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ab380c5
Merge pull request #39 from tristan-deep/waterloo-femoralvein-hub-paths
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fb4a674
Fix Twente vortexflow RF channel count
rienkcz Sep 24, 2026
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twente-vortexflow: simplify reconstruct.py, grid and dynamic range in…
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d427864
twente-vortexflow: build the pipeline in code again
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Add license conversion note in README
PengJin95 Sep 24, 2026
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ulmshare: tidy reconstruct.py logging and cap the Power-Doppler movie
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3747070
ulmshare: add hero and main images
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156 changes: 79 additions & 77 deletions datasets/colorado-boulder/README.md
Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
---
pretty_name: "OpenH-RF — Tracked Swept Synthetic Aperture 3D Phantom Dataset"
name: colorado-boulder
pretty_name: "Tracked Swept Synthetic Aperture Ultrasound Datasets"
license: cc-by-4.0
task_categories:
- generalized-reconstruction
Expand All @@ -14,63 +15,89 @@ size_categories:
- n<1K
---

# Tracked Swept Synthetic Aperture 3D Phantom Ultrasound Dataset
# Tracked Swept Synthetic Aperture Ultrasound Datasets

## Dataset Description
| 2D ATS 539 phantom | 3D phantom | In-vivo quadriceps |
|:---:|:---:|:---:|
| ![Tracked SSA sweep through the 2D ATS 539 phantom](assets/ssa-sweep-phantom2d.gif) | ![Tracked SSA sweep through the 3D phantom](assets/ssa-sweep-phantom3d.gif) | ![Tracked SSA sweep along in-vivo quadriceps muscle](assets/ssa-sweep-invivo.gif) |
| [`Sub-dataset-1`](https://huggingface.co/datasets/nvidia/OpenH-RF/tree/main/colorado-boulder/Sub-dataset-1) | [`Sub-dataset-2`](https://huggingface.co/datasets/nvidia/OpenH-RF/tree/main/colorado-boulder/Sub-dataset-2) | [`Sub-dataset-3`](https://huggingface.co/datasets/nvidia/OpenH-RF/tree/main/colorado-boulder/Sub-dataset-3) |

This dataset contains tracked swept synthetic aperture (SSA) ultrasound acquisitions of a 3D ultrasound imaging phantom. The data were acquired using a Verasonics Vantage research ultrasound system with a P4-2 phased array transducer.
*Motion-compensated tracked SSA reconstructions, one per sub-dataset. Each frame beamforms the raw RF channel data with its own tracked probe pose; a 40 mm window of frames is then coherently summed to synthesise a larger effective aperture, and the window slides along the freehand sweep.*

The dataset includes raw RF channel data, acquisition parameters, probe geometry, transmit information, and frame-wise tracked probe pose metadata. Its purpose is to provide a reproducible example of motion-compensated SSA reconstruction from raw channel data using the zea/OpenH-RF data format.
## Dataset Description

This dataset contains phantom data only. It does not contain human subject data, animal data, or protected health information (PHI).
This dataset contains tracked swept synthetic aperture (SSA) ultrasound acquisitions from three targets: a 2D ATS 539 multipurpose imaging phantom, a 3D ultrasound imaging phantom, and in-vivo quadriceps muscle from healthy volunteer participants.

## Dataset Contributor(s)
The data were acquired using a Verasonics Vantage research ultrasound system with a P4-2 phased array transducer. The dataset includes raw RF channel data, acquisition parameters, probe geometry, transmit information, and frame-wise tracked probe pose metadata.

**Contributing organization:** University of Colorado Boulder, Bottenus Lab
The purpose of this dataset is to provide reproducible examples for generalized ultrasound reconstruction, with a particular focus on motion-compensated tracked SSA reconstruction using the zea/OpenH-RF data format.

**Contributors:**
The phantom acquisitions do not contain human subject data, animal data, or protected health information (PHI). The in-vivo acquisitions were collected from healthy volunteer participants and de-identified prior to release.

- Anet Sanchez
- Nick Bottenus
## Dataset Contributor(s)

- Anet Sanchez (University of Colorado Boulder, Bottenus Lab)
- Nick Bottenus (University of Colorado Boulder, Bottenus Lab)

## Dataset Creation Date

06/24/2025
Data were collected between 08/23/2024 and 06/30/2026.

## License / Terms of Use

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

The contributed data consist exclusively of phantom ultrasound acquisitions and are cleared for release under CC BY 4.0. Patient consent, clinical data-use agreements, and PHI de-identification are not applicable because the dataset does not contain human subject data.
[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/legalcode.en). Retain attribution and identify modifications when reusing the data.

## Intended Usage

This dataset is intended for research on generalized ultrasound reconstruction, with a particular focus on tracked swept synthetic aperture imaging, motion-compensated beamforming, coherent compounding, and ultrasound image-quality evaluation.
This dataset is intended for research on generalized ultrasound reconstruction, with a specific focus on tracked swept synthetic aperture imaging, motion-compensated beamforming, coherent compounding, and ultrasound image-quality evaluation.

For SSA reconstruction, each raw RF frame is beamformed using its corresponding tracked transducer pose. The resulting beamformed IQ frames are placed on a common reconstruction grid and coherently summed to synthesize a larger effective aperture. Because the reconstruction relies on coherent compounding, summation is performed before envelope detection, normalization, and log compression.
For SSA reconstruction, each raw RF frame is beamformed using its corresponding tracked transducer pose. The resulting beamformed frames are placed on a common reconstruction grid and coherently summed to synthesize a larger effective aperture. Because the reconstruction relies on coherent compounding, summation is performed before envelope detection, normalization, and log compression.

## Dataset Characterization

- **Data Collection Method:** Phantom ultrasound acquisition
- **Labeling Method:** N/A; no manual labels or segmentation masks are provided
- **Acquisition System:** Verasonics Vantage research ultrasound scanner with a Verasonics P4-2 phased array transducer
The dataset includes acquisitions from three targets:

- 2D ATS 539 multipurpose imaging phantom
- 3D ultrasound imaging phantom
- In-vivo quadriceps muscle from healthy volunteer participants

The ATS 539 multipurpose imaging phantom contains:

- Wire targets
- Cylindrical lesions
- Tissue-mimicking speckle regions

These targets may be used to assess spatial resolution, contrast, lesion visibility, and speckle characteristics.

### Data Collection Method

Each acquisition consisted of a freehand sweep in the lateral direciton of the transducer. All 64 array elements were used during receive. Diverging waves were generated using a negative virtual source while activating the 20 central array elements during transmit. For in-vivo targets the transducer was manually swept along the longitudinal direction of the quadriceps while transmitting diverging waves at 400 Hz. The transducer was optically tracked using an NDI Polaris Vega® XT optical tracking system manufactured by Northern Digital Inc., Ontario, Canada.

### Labeling Method

### Acquisition Details
None (N/A).

The transducer was manually swept over the phantom field of view while diverging-wave transmissions were acquired at 400 Hz. All 64 array elements were used on receive.
### Acquisition System

Diverging waves were generated using a negative virtual source with the 20 central array elements active on transmit.
- Verasonics Vantage research ultrasound scanner
- Verasonics P4-2 phased array transducer
- 64 elements
- Reconstruction center frequency: 2.5 MHz
- Sampling frequency: 10 MHz
- Optical tracking: NDI Polaris Vega XT

The transducer was optically tracked using an NDI Polaris Vega® XT optical tracking system manufactured by Northern Digital Inc., Ontario, Canada.
## Processing the Dataset

### Probe and Geometry
The acquisitions can be processed with the `reconstruct.py` [script](https://github.com/open-h/OpenH-RF/blob/main/datasets/colorado-boulder/reconstruct.py) as provided in the [OpenH-RF GitHub repository](https://github.com/open-h/OpenH-RF), together with the `pipeline.yaml` definition in this folder and the [zea library](https://github.com/tue-bmd/zea). The script streams the data from the Hugging Face Hub.

The acquisition used a Verasonics P4-2 phased array transducer with 64 elements. The center frequency stored in the acquisition and used for reconstruction is 2.5 MHz.
The script selects tracked frames at roughly 1 mm lateral spacing and writes the reconstruction to `ssa_bmode.png`. Point `ZEA_FILE` at any acquisition in the corpus to reconstruct it. [`assets/main_bmode.png`](./assets/main_bmode.png) was produced this way, compounding the full sweep into one image; the loops at the top of this card slide a shorter aperture window along the sweep instead.

The probe geometry, transmit origins, transmit delays, transmit apodization, and other acquisition parameters are stored in the zea/OpenH-RF file. Frame-wise probe translations and rotations are stored using the native `metadata/probe_pose` structure.
`reconstruct.py` defines the custom `apply_probe_pose` operation that `pipeline.yaml` refers to, which applies the frame-wise `metadata/probe_pose` to the probe geometry and transmit origins before beamforming.

## Dataset Format

[zea v0.1.7](https://github.com/tue-bmd/zea)

The dataset is distributed in the zea/OpenH-RF HDF5 format.

Each file includes:
Expand All @@ -84,20 +111,19 @@ Each file includes:
- Frame-wise tracked probe translations
- Frame-wise tracked probe rotations

The stored RF channel data have not been beamformed, envelope detected, normalized, or log compressed. The accompanying reconstruction pipeline performs these processing steps.
The stored RF channel data have not been beamformed, demodulated, envelope detected, normalized, or log compressed. These processing steps are performed by the accompanying reconstruction pipeline.

## Dataset Quantification

**Current OpenH-RF release:** 62 HDF5 files; 16.04 GB (16,037,117,952 bytes) stored; root `zea_version` **0.1.6**. Sizes include all HDF5 contents and use decimal units (MB = 10^6 bytes, GB = 10^9 bytes, TB = 10^12 bytes), not decoded-array memory or original-source download sizes.

- **Number of phantom objects:** 1
- **Number of acquisitions:** 10
- **Number of RF frames per acquisition:** 1200
- **Number of transmit events per frame:** 1
- **Number of receive elements:** 64
- **Number of active transmit elements:** 20
- Number of phantom objects: 2
- Number of volunteer participants: 7
- Number of acquisitions: 62
- Number of RF frames per acquisition: 1200–1600
- Number of transmit events per frame: 1
- Number of receive elements: 64
- Number of active transmit elements: 20

### Per-File Feature Summary
### Per-acquisition contents

| Feature | Shape | Data type | Units | Description |
|---|---:|---|---|---|
Expand All @@ -111,64 +137,40 @@ The stored RF channel data have not been beamformed, envelope detected, normaliz

## Subject Metadata

### Metadata Schema Migration

The zea 0.1.6 migration uses these approved metadata locations:

| Legacy location | Canonical location |
|---|---|
| Dataset `metadata/subject_id` | Dataset `metadata/subject/id` |
| Dataset `metadata/subject_type` | Dataset `metadata/subject/type` |
| Dataset `metadata/us_machine` | Root HDF5 attribute `us_machine` |

Read the machine name with `f.attrs["us_machine"]`, not `f["us_machine"]`.
Subject values and their existing attributes are preserved. The machine
string is preserved; migration stops for review if its legacy dataset has
attributes that cannot be represented without loss. No numerical arrays are
rescaled or otherwise changed by these relocations.

The three-field pilot passed full array and metadata parity checks with the
approved description changes and `transmit_only=False` default. Full-release
migration is still pending. Replacement files are uploaded only after
per-file validation; readers supporting both revisions should check the
canonical locations first, then the legacy locations.
This dataset contains acquisitions from two ultrasound imaging phantoms and healthy volunteer participants.


This dataset contains one 3D ultrasound imaging phantom.

- **Subject type:** 3D phantom
- **Anatomical region:** Not applicable
- **Human participants:** None
- **Animal subjects:** None
- **Protected health information:** None
- **Scanner:** Verasonics Vantage
- **Probe:** Verasonics P4-2 phased array
- Subject types: 2D imaging phantom, 3D phantom, and in-vivo human ultrasound data
- 2D phantom model: ATS 539
- 2D phantom target types: wires, cylindrical lesions, and tissue-mimicking speckle
- In-vivo anatomical region: quadriceps muscle
- Human participants: healthy volunteer participants for the in-vivo dataset
- Animal subjects: None
- Protected health information: None
- Scanner: Verasonics Vantage
- Probe: Verasonics P4-2 phased array

## Data Validation

The submission includes a `zea.Pipeline` that reconstructs a representative tracked SSA B-mode image from the raw RF channel data.
The submission includes a `zea.Pipeline` that reconstructs representative tracked SSA B-mode images from the raw RF channel data.

The pipeline performs:

1. Frame-wise demodulation
2. Application of the tracked probe pose
3. Delay-and-sum beamforming onto a common reconstruction grid
4. Coherent summation of the beamformed IQ frames
4. Coherent SSA compounding
5. Envelope detection
6. Normalization
7. Log compression

The reconstruction is defined in `pipeline.yaml` and executed using `reconstruct.py`. A representative reconstructed B-mode image is included with the dataset.

## Known Issues

- Optical tracking measurements may contain small position and orientation uncertainties.
- Reconstruction quality depends on tracking calibration accuracy and coherent alignment between frames.

- The in-vivo dataset is intended for research use and has not been optimized for clinical workflows.

## Ethical Considerations

This dataset contains phantom ultrasound data only. It does not contain human participants, animal subjects, personal identifiers, clinical records, or protected health information.

Human-subject consent and institutional review board approval are therefore not applicable.

- **Phantom data:** phantom ultrasound acquisitions only — no human participants, animal subjects, personal identifiers or clinical records; consent and IRB approval are not applicable.
- **In-vivo data:** acquired from healthy volunteer participants with informed consent under IRB-approved protocol #24-0176, and de-identified prior to release.
- No protected health information (PHI) or participant-identifying metadata is included in the released files.
Binary file added datasets/colorado-boulder/assets/main_bmode.png
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