Add oslo README + pipeline(s) from accepted_submissions

oslo/A_cardiac/README.md

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+---
+pretty_name: "USTB - In-vivo Cardiac (Verasonics P4-2)"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - cardiac
+  - in-vivo
+size_categories:
+  - n<1K
+---
+
+# USTB - In-vivo Cardiac (Verasonics P4-2)
+
+Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** contributed to the
+[OpenH-RF](https://github.com/open-h/OpenH-RF) initiative. All acquisitions are stored in the
+*zea* HDF5 file format (zea_version 0.1.0) and contain raw pre-beamformed
+channel data (`/data/raw_data`).
+
+## Dataset Description
+
+In-vivo human cardiac channel-capture data acquired with a Verasonics Vantage 256 research scanner and a P4-2 phased-array probe. The collection contains parasternal long-axis and apical four-chamber views recorded with focused transmit beams (sector scan). The data is pre-beamformed RF channel data intended for research into generalized beamforming, adaptive imaging and cardiac reconstruction.
+
+## Dataset Contributors
+
+University of Oslo (UiO), Department of Informatics. Primary contact: Ole Marius Hoel Rindal (omrindal@ifi.uio.no). Team: Ole Marius Hoel Rindal, Yucel Karabiyik, Sven Peter Nasholm, Andreas Austeng.
+
+## Dataset Creation Date
+
+06/23/2026 (packaging date; original acquisitions/simulations were produced between 2016 and 2023).
+
+## License / Terms of Use
+
+Released under **Creative Commons Attribution 4.0 International (CC BY 4.0)** — see the `LICENCE`
+file at the submission root (this license is also declared in the YAML frontmatter above). The
+contributed data is cleared for this license. The UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo. Contributed to OpenH-RF. Zenodo record 20261898.
+
+## Intended Usage
+
+Generalized reconstruction and adaptive beamforming of cardiac ultrasound (RFP task 6.1). Suitable for B-mode reconstruction, aperture-domain processing, and deep-learning beamforming research on in-vivo cardiac data. (OpenH-RF RFP task 6.1 Generalized Reconstruction).
+
+## Dataset Characterization
+
+- **Data Collection Method:** clinical
+- **Labeling Method:** N/A (raw channel data; no annotations).
+- **Acquisition system:** probe(s) P4-2;
+  element positions stored in `/probe/probe_geometry` (meters); center frequency, sampling
+  frequency and sound speed stored per acquisition in `/scan` (see per-sample feature table).
+
+## Dataset Format
+
+All acquisitions are stored in the **zea** HDF5 file format. Each `.hdf5` file is a single
+acquisition with raw channel data `/data/raw_data` of shape
+`(n_frames, n_tx, n_ax, n_el, n_ch)` and a fully populated `/scan` group describing the transmit
+sequence (delays, focus distances, steering angles, apodization, timing). Data type: RF (n_ch=1).
+No demodulation or decimation was applied during packaging beyond conversion from the USTB
+Ultrasound File Format (UFF) to zea; RF data is demodulated inside the reconstruction pipeline.
+
+## Dataset Quantification
+
+- **Number of acquisitions:** 2
+- **Total channel-capture frames:** 75
+- **Train / validation / test split:** not predefined (research dataset).
+- **Total size on disk:** 4095 MB
+
+Per-acquisition summary:
+
+| Acquisition | frames | transmits | samples | elements | n_ch | fs (MHz) | fc (MHz) | size (MB) |
+|---|---|---|---|---|---|---|---|---|
+| `Verasonics_P2-4_apical_four_chamber_subject_1` | 25 | 101 | 2176 | 64 | 1 | 11.9 | 2.98 | 1366 |
+| `Verasonics_P2-4_parasternal_long_subject_1` | 50 | 101 | 2176 | 64 | 1 | 11.9 | 2.98 | 2729 |
+
+Per-sample feature table:
+
+| Field | Shape | Dtype | Units | Description |
+|---|---|---|---|---|
+| `data/raw_data` | `(n_frames, n_tx, n_ax, n_el, n_ch)` | float32 | a.u. | Raw pre-beamformed RF channel data |
+| `scan/sampling_frequency` | `scalar` | float32 | Hz | A/D sampling frequency |
+| `scan/center_frequency` | `scalar` | float32 | Hz | Transmit pulse center frequency |
+| `scan/demodulation_frequency` | `scalar` | float32 | Hz | Demodulation (carrier) frequency |
+| `scan/sound_speed` | `scalar` | float32 | m/s | Assumed medium speed of sound |
+| `scan/initial_times` | `(n_tx,)` | float32 | s | A/D start time per transmit |
+| `scan/t0_delays` | `(n_tx, n_el)` | float32 | s | Per-element transmit fire times |
+| `scan/tx_apodizations` | `(n_tx, n_el)` | float32 | - | Per-element transmit apodization |
+| `scan/focus_distances` | `(n_tx,)` | float32 | m | Focus distance per transmit (0 = plane wave) |
+| `scan/polar_angles` | `(n_tx,)` | float32 | rad | Transmit steering (polar) angle |
+| `scan/transmit_origins` | `(n_tx, 3)` | float32 | m | Transmit beam origin (x, y, z) |
+| `probe/probe_geometry` | `(n_el, 3)` | float32 | m | Element positions (x, y, z) |
+
+## Subject Metadata
+
+Healthy adult volunteer(s). Anatomy: heart (parasternal long-axis, apical four-chamber). Scanner: Verasonics Vantage 256. Probe: P4-2 phased array (64 elements). Aggregate only; no per-subject identifiers are stored.
+
+## Data Validation
+
+A Delay-And-Sum `zea.Pipeline` is provided in the **`pipeline.yaml` at the submission root** and
+run by the single **`reconstruct.py` at the submission root**:
+`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`
+(RF is demodulated in-pipeline; IQ uses a baseband pipeline). The script is geometry-driven and
+recurses into every sub-dataset folder; running `python reconstruct.py` from the root reconstructs
+every `.hdf5` in the collection (or pass a folder-qualified path for a single acquisition) and writes
+`<name>_zea_bmode.png` next to each file as a portable check that the recorded geometry and timing
+are correct.
+
+The reference B-mode images committed alongside the data (`<name>_bmode.png`) are produced with the
+UltraSound ToolBox (USTB) MATLAB Delay-And-Sum beamformer — the exact per-dataset reconstruction
+used in the public USTB dataset catalog (https://unioslo.github.io/USTB/datasets.html), with
+scanline transmit apodization for focused/sector acquisitions and correct sector-scan geometry.
+These are the recommended reference reconstructions for visual verification.
+
+## Known Issues
+
+Focused sector acquisition: lateral resolution and field of view follow the transmit geometry. Phased-array data is best reconstructed on a polar (sector) grid. Frame counts vary per acquisition.
+
+## Ethical Considerations
+
+In-vivo data recorded from healthy adult volunteers at the University of Oslo with written informed consent for research use and data sharing, and approval from the Regional Committee for Medical and Health Research Ethics (REK), Norway. The files contain only backscattered RF channel data and acquisition parameters - no patient name, identifier, date of birth, acquisition date, facial image, or any other HHS Safe Harbor identifier is present (de-identified by construction).

oslo/B_carotid/README.md

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+---
+pretty_name: "USTB - In-vivo Carotid (Verasonics L7-4)"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - vascular
+  - carotid
+  - in-vivo
+size_categories:
+  - n<1K
+---
+
+# USTB - In-vivo Carotid (Verasonics L7-4)
+
+Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** contributed to the
+[OpenH-RF](https://github.com/open-h/OpenH-RF) initiative. All acquisitions are stored in the
+*zea* HDF5 file format (zea_version 0.1.0) and contain raw pre-beamformed
+channel data (`/data/raw_data`).
+
+## Dataset Description
+
+In-vivo human carotid-artery channel-capture data acquired with a Verasonics Vantage 256 and an L7-4 linear-array probe, cross-sectional views, focused transmit imaging. Pre-beamformed RF channel data for vascular imaging and beamforming research.
+
+## Dataset Contributors
+
+University of Oslo (UiO), Department of Informatics. Primary contact: Ole Marius Hoel Rindal (omrindal@ifi.uio.no). Team: Ole Marius Hoel Rindal, Yucel Karabiyik, Sven Peter Nasholm, Andreas Austeng.
+
+## Dataset Creation Date
+
+06/23/2026 (packaging date; original acquisitions/simulations were produced between 2016 and 2023).
+
+## License / Terms of Use
+
+Released under **Creative Commons Attribution 4.0 International (CC BY 4.0)** — see the `LICENCE`
+file at the submission root (this license is also declared in the YAML frontmatter above). The
+contributed data is cleared for this license. The UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo. Contributed to OpenH-RF. Zenodo record 20261898.
+
+## Intended Usage
+
+Generalized reconstruction and adaptive beamforming of vascular ultrasound (RFP task 6.1). (OpenH-RF RFP task 6.1 Generalized Reconstruction).
+
+## Dataset Characterization
+
+- **Data Collection Method:** clinical
+- **Labeling Method:** N/A (raw channel data; no annotations).
+- **Acquisition system:** probe(s) L7-4;
+  element positions stored in `/probe/probe_geometry` (meters); center frequency, sampling
+  frequency and sound speed stored per acquisition in `/scan` (see per-sample feature table).
+
+## Dataset Format
+
+All acquisitions are stored in the **zea** HDF5 file format. Each `.hdf5` file is a single
+acquisition with raw channel data `/data/raw_data` of shape
+`(n_frames, n_tx, n_ax, n_el, n_ch)` and a fully populated `/scan` group describing the transmit
+sequence (delays, focus distances, steering angles, apodization, timing). Data type: RF (n_ch=1).
+No demodulation or decimation was applied during packaging beyond conversion from the USTB
+Ultrasound File Format (UFF) to zea; RF data is demodulated inside the reconstruction pipeline.
+
+## Dataset Quantification
+
+- **Number of acquisitions:** 3
+- **Total channel-capture frames:** 6
+- **Train / validation / test split:** not predefined (research dataset).
+- **Total size on disk:** 396 MB
+
+Per-acquisition summary:
+
+| Acquisition | frames | transmits | samples | elements | n_ch | fs (MHz) | fc (MHz) | size (MB) |
+|---|---|---|---|---|---|---|---|---|
+| `L7_FI_carotid_cross_1` | 2 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 141 |
+| `L7_FI_carotid_cross_2` | 2 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 127 |
+| `L7_FI_carotid_cross_sub_2` | 2 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 128 |
+
+Per-sample feature table:
+
+| Field | Shape | Dtype | Units | Description |
+|---|---|---|---|---|
+| `data/raw_data` | `(n_frames, n_tx, n_ax, n_el, n_ch)` | float32 | a.u. | Raw pre-beamformed RF channel data |
+| `scan/sampling_frequency` | `scalar` | float32 | Hz | A/D sampling frequency |
+| `scan/center_frequency` | `scalar` | float32 | Hz | Transmit pulse center frequency |
+| `scan/demodulation_frequency` | `scalar` | float32 | Hz | Demodulation (carrier) frequency |
+| `scan/sound_speed` | `scalar` | float32 | m/s | Assumed medium speed of sound |
+| `scan/initial_times` | `(n_tx,)` | float32 | s | A/D start time per transmit |
+| `scan/t0_delays` | `(n_tx, n_el)` | float32 | s | Per-element transmit fire times |
+| `scan/tx_apodizations` | `(n_tx, n_el)` | float32 | - | Per-element transmit apodization |
+| `scan/focus_distances` | `(n_tx,)` | float32 | m | Focus distance per transmit (0 = plane wave) |
+| `scan/polar_angles` | `(n_tx,)` | float32 | rad | Transmit steering (polar) angle |
+| `scan/transmit_origins` | `(n_tx, 3)` | float32 | m | Transmit beam origin (x, y, z) |
+| `probe/probe_geometry` | `(n_el, 3)` | float32 | m | Element positions (x, y, z) |
+
+## Subject Metadata
+
+Healthy adult volunteer(s). Anatomy: carotid artery (cross-section). Scanner: Verasonics Vantage 256. Probe: L7-4 linear array (128 elements). Aggregate only; no per-subject identifiers.
+
+## Data Validation
+
+A Delay-And-Sum `zea.Pipeline` is provided in the **`pipeline.yaml` at the submission root** and
+run by the single **`reconstruct.py` at the submission root**:
+`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`
+(RF is demodulated in-pipeline; IQ uses a baseband pipeline). The script is geometry-driven and
+recurses into every sub-dataset folder; running `python reconstruct.py` from the root reconstructs
+every `.hdf5` in the collection (or pass a folder-qualified path for a single acquisition) and writes
+`<name>_zea_bmode.png` next to each file as a portable check that the recorded geometry and timing
+are correct.
+
+The reference B-mode images committed alongside the data (`<name>_bmode.png`) are produced with the
+UltraSound ToolBox (USTB) MATLAB Delay-And-Sum beamformer — the exact per-dataset reconstruction
+used in the public USTB dataset catalog (https://unioslo.github.io/USTB/datasets.html), with
+scanline transmit apodization for focused/sector acquisitions and correct sector-scan geometry.
+These are the recommended reference reconstructions for visual verification.
+
+## Known Issues
+
+Single/few-frame acquisitions; focused linear imaging.
+
+## Ethical Considerations
+
+In-vivo data recorded from healthy adult volunteers at the University of Oslo with written informed consent for research use and data sharing, and approval from the Regional Committee for Medical and Health Research Ethics (REK), Norway. Files contain only RF channel data and acquisition parameters; no HHS Safe Harbor identifiers are present.

oslo/C_verasonics_phantom/README.md

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+---
+pretty_name: "USTB - Phantom (Verasonics L7-4 / P4)"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - phantom
+  - cirs
+size_categories:
+  - n<1K
+---
+
+# USTB - Phantom (Verasonics L7-4 / P4)
+
+Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** contributed to the
+[OpenH-RF](https://github.com/open-h/OpenH-RF) initiative. All acquisitions are stored in the
+*zea* HDF5 file format (zea_version 0.1.0) and contain raw pre-beamformed
+channel data (`/data/raw_data`).
+
+## Dataset Description
+
+Tissue-mimicking and table-top phantom channel-capture data acquired on a Verasonics Vantage 256 with L7-4 linear and P4 phased-array probes. The collection spans coherent plane-wave compounding (CPWC), focused imaging (FI), synthetic transmit aperture (STA) and diverging-wave (DW) sequences for resolution, contrast, dynamic-range and point-spread-function evaluation, including CIRS tissue-mimicking phantom targets.
+
+## Dataset Contributors
+
+University of Oslo (UiO), Department of Informatics. Primary contact: Ole Marius Hoel Rindal (omrindal@ifi.uio.no). Team: Ole Marius Hoel Rindal, Yucel Karabiyik, Sven Peter Nasholm, Andreas Austeng.
+
+## Dataset Creation Date
+
+06/23/2026 (packaging date; original acquisitions/simulations were produced between 2016 and 2023).
+
+## License / Terms of Use
+
+Released under **Creative Commons Attribution 4.0 International (CC BY 4.0)** — see the `LICENCE`
+file at the submission root (this license is also declared in the YAML frontmatter above). The
+contributed data is cleared for this license. The UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo. Contributed to OpenH-RF. Zenodo record 20261898.
+
+## Intended Usage
+
+Generalized reconstruction, image-quality assessment (resolution, contrast, dynamic range), and beamforming research (RFP task 6.1). Several acquisitions provide multiple transmit schemes on the same target for cross-method comparison. (OpenH-RF RFP task 6.1 Generalized Reconstruction).
+
+## Dataset Characterization
+
+- **Data Collection Method:** phantom
+- **Labeling Method:** Derived (known phantom geometry, e.g. CIRS Model 040GSE where applicable).
+- **Acquisition system:** probe(s) L7-4, P4-1, P4-2;
+  element positions stored in `/probe/probe_geometry` (meters); center frequency, sampling
+  frequency and sound speed stored per acquisition in `/scan` (see per-sample feature table).
+
+## Dataset Format
+
+All acquisitions are stored in the **zea** HDF5 file format. Each `.hdf5` file is a single
+acquisition with raw channel data `/data/raw_data` of shape
+`(n_frames, n_tx, n_ax, n_el, n_ch)` and a fully populated `/scan` group describing the transmit
+sequence (delays, focus distances, steering angles, apodization, timing). Data type: RF (n_ch=1).
+No demodulation or decimation was applied during packaging beyond conversion from the USTB
+Ultrasound File Format (UFF) to zea; RF data is demodulated inside the reconstruction pipeline.
+
+## Dataset Quantification
+
+- **Number of acquisitions:** 15
+- **Total channel-capture frames:** 27
+- **Train / validation / test split:** not predefined (research dataset).
+- **Total size on disk:** 1448 MB
+
+Per-acquisition summary:
+
+| Acquisition | frames | transmits | samples | elements | n_ch | fs (MHz) | fc (MHz) | size (MB) |
+|---|---|---|---|---|---|---|---|---|
+| `experimental_dynamic_range_phantom` | 1 | 128 | 3840 | 128 | 1 | 40.8 | 5.00 | 252 |
+| `experimental_STAI_dynamic_range` | 1 | 128 | 1920 | 128 | 1 | 20.4 | 5.00 | 125 |
+| `FI_P4_cysts_center` | 1 | 128 | 2048 | 64 | 1 | 10.9 | 2.72 | 38 |
+| `FI_P4_point_scatterers` | 6 | 128 | 1792 | 64 | 1 | 10.9 | 2.72 | 195 |
+| `L7_CPWC_193328` | 3 | 15 | 1920 | 128 | 1 | 20.8 | 5.20 | 30 |
+| `L7_CPWC_TheGB` | 1 | 11 | 1920 | 128 | 1 | 20.8 | 5.00 | 7 |
+| `L7_DW_TheGB` | 1 | 25 | 1920 | 128 | 1 | 20.8 | 5.21 | 14 |
+| `L7_FI_IUS2018` | 1 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 62 |
+| `L7_FI_TheGB` | 1 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 61 |
+| `L7_FI_Verasonics` | 1 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 125 |
+| `L7_FI_Verasonics_CIRS` | 1 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 125 |
+| `L7_FI_Verasonics_CIRS_points` | 1 | 128 | 1920 | 128 | 1 | 20.8 | 5.21 | 125 |
+| `L7_STA_TheGB` | 1 | 128 | 1920 | 128 | 1 | 20.8 | 5.00 | 60 |
+| `P4_FI_121444_45mm_focus` | 6 | 128 | 1280 | 64 | 1 | 11.9 | 2.98 | 151 |
+| `STAI_UFF_CIRS_phantom` | 1 | 128 | 2688 | 128 | 1 | 20.8 | 5.00 | 78 |
+
+Per-sample feature table:
+
+| Field | Shape | Dtype | Units | Description |
+|---|---|---|---|---|
+| `data/raw_data` | `(n_frames, n_tx, n_ax, n_el, n_ch)` | float32 | a.u. | Raw pre-beamformed RF channel data |
+| `scan/sampling_frequency` | `scalar` | float32 | Hz | A/D sampling frequency |
+| `scan/center_frequency` | `scalar` | float32 | Hz | Transmit pulse center frequency |
+| `scan/demodulation_frequency` | `scalar` | float32 | Hz | Demodulation (carrier) frequency |
+| `scan/sound_speed` | `scalar` | float32 | m/s | Assumed medium speed of sound |
+| `scan/initial_times` | `(n_tx,)` | float32 | s | A/D start time per transmit |
+| `scan/t0_delays` | `(n_tx, n_el)` | float32 | s | Per-element transmit fire times |
+| `scan/tx_apodizations` | `(n_tx, n_el)` | float32 | - | Per-element transmit apodization |
+| `scan/focus_distances` | `(n_tx,)` | float32 | m | Focus distance per transmit (0 = plane wave) |
+| `scan/polar_angles` | `(n_tx,)` | float32 | rad | Transmit steering (polar) angle |
+| `scan/transmit_origins` | `(n_tx, 3)` | float32 | m | Transmit beam origin (x, y, z) |
+| `probe/probe_geometry` | `(n_el, 3)` | float32 | m | Element positions (x, y, z) |
+
+## Subject Metadata
+
+No human or animal subjects. Targets: CIRS tissue-mimicking phantoms and lab phantoms (wire/point targets, hypo/hyperechoic inclusions, dynamic-range targets). Probes: L7-4 (128 el.), P4 phased array.
+
+## Data Validation
+
+A Delay-And-Sum `zea.Pipeline` is provided in the **`pipeline.yaml` at the submission root** and
+run by the single **`reconstruct.py` at the submission root**:
+`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`
+(RF is demodulated in-pipeline; IQ uses a baseband pipeline). The script is geometry-driven and
+recurses into every sub-dataset folder; running `python reconstruct.py` from the root reconstructs
+every `.hdf5` in the collection (or pass a folder-qualified path for a single acquisition) and writes
+`<name>_zea_bmode.png` next to each file as a portable check that the recorded geometry and timing
+are correct.
+
+The reference B-mode images committed alongside the data (`<name>_bmode.png`) are produced with the
+UltraSound ToolBox (USTB) MATLAB Delay-And-Sum beamformer — the exact per-dataset reconstruction
+used in the public USTB dataset catalog (https://unioslo.github.io/USTB/datasets.html), with
+scanline transmit apodization for focused/sector acquisitions and correct sector-scan geometry.
+These are the recommended reference reconstructions for visual verification.
+
+## Known Issues
+
+Mixed transmit schemes across files (CPWC / FI / STA / DW). Single-frame acquisitions for most phantoms. The reference reconstruction uses a single B-mode pipeline; per-scheme tuning may improve image quality.
+
+## Ethical Considerations
+
+Phantom / table-top acquisitions; no human or animal subjects are involved. No ethical considerations beyond standard laboratory practice.

oslo/D_alpinion_phantom/README.md

@@ -0,0 +1,124 @@
+---
+pretty_name: "USTB - Phantom (Alpinion L3-8)"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - phantom
+  - alpinion
+size_categories:
+  - n<1K
+---
+
+# USTB - Phantom (Alpinion L3-8)
+
+Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** contributed to the
+[OpenH-RF](https://github.com/open-h/OpenH-RF) initiative. All acquisitions are stored in the
+*zea* HDF5 file format (zea_version 0.1.0) and contain raw pre-beamformed
+channel data (`/data/raw_data`).
+
+## Dataset Description
+
+Phantom channel-capture data acquired on an Alpinion E-Cube 12R research scanner with an L3-8 linear-array probe. Hypoechoic and hyperechoic targets imaged with focused (FI) and coherent plane-wave compounding (CPWC) sequences.
+
+## Dataset Contributors
+
+University of Oslo (UiO), Department of Informatics. Primary contact: Ole Marius Hoel Rindal (omrindal@ifi.uio.no). Team: Ole Marius Hoel Rindal, Yucel Karabiyik, Sven Peter Nasholm, Andreas Austeng.
+
+## Dataset Creation Date
+
+06/23/2026 (packaging date; original acquisitions/simulations were produced between 2016 and 2023).
+
+## License / Terms of Use
+
+Released under **Creative Commons Attribution 4.0 International (CC BY 4.0)** — see the `LICENCE`
+file at the submission root (this license is also declared in the YAML frontmatter above). The
+contributed data is cleared for this license. The UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo. Contributed to OpenH-RF. Zenodo record 20261898.
+
+## Intended Usage
+
+Generalized reconstruction and image-quality assessment on a second hardware platform (RFP task 6.1); cross-vendor robustness studies. (OpenH-RF RFP task 6.1 Generalized Reconstruction).
+
+## Dataset Characterization
+
+- **Data Collection Method:** phantom
+- **Labeling Method:** Derived (known phantom target types).
+- **Acquisition system:** probe(s) L3-8;
+  element positions stored in `/probe/probe_geometry` (meters); center frequency, sampling
+  frequency and sound speed stored per acquisition in `/scan` (see per-sample feature table).
+
+## Dataset Format
+
+All acquisitions are stored in the **zea** HDF5 file format. Each `.hdf5` file is a single
+acquisition with raw channel data `/data/raw_data` of shape
+`(n_frames, n_tx, n_ax, n_el, n_ch)` and a fully populated `/scan` group describing the transmit
+sequence (delays, focus distances, steering angles, apodization, timing). Data type: RF (n_ch=1).
+No demodulation or decimation was applied during packaging beyond conversion from the USTB
+Ultrasound File Format (UFF) to zea; RF data is demodulated inside the reconstruction pipeline.
+
+## Dataset Quantification
+
+- **Number of acquisitions:** 4
+- **Total channel-capture frames:** 4
+- **Train / validation / test split:** not predefined (research dataset).
+- **Total size on disk:** 505 MB
+
+Per-acquisition summary:
+
+| Acquisition | frames | transmits | samples | elements | n_ch | fs (MHz) | fc (MHz) | size (MB) |
+|---|---|---|---|---|---|---|---|---|
+| `Alpinion_L3-8_CPWC_hyperechoic_scatterers` | 1 | 21 | 4352 | 128 | 1 | 40.0 | 6.00 | 47 |
+| `Alpinion_L3-8_CPWC_hypoechoic` | 1 | 21 | 4352 | 128 | 1 | 40.0 | 6.00 | 47 |
+| `Alpinion_L3-8_FI_hyperechoic_scatterers` | 1 | 256 | 3474 | 128 | 1 | 40.0 | 6.00 | 206 |
+| `Alpinion_L3-8_FI_hypoechoic` | 1 | 256 | 3474 | 128 | 1 | 40.0 | 6.00 | 206 |
+
+Per-sample feature table:
+
+| Field | Shape | Dtype | Units | Description |
+|---|---|---|---|---|
+| `data/raw_data` | `(n_frames, n_tx, n_ax, n_el, n_ch)` | float32 | a.u. | Raw pre-beamformed RF channel data |
+| `scan/sampling_frequency` | `scalar` | float32 | Hz | A/D sampling frequency |
+| `scan/center_frequency` | `scalar` | float32 | Hz | Transmit pulse center frequency |
+| `scan/demodulation_frequency` | `scalar` | float32 | Hz | Demodulation (carrier) frequency |
+| `scan/sound_speed` | `scalar` | float32 | m/s | Assumed medium speed of sound |
+| `scan/initial_times` | `(n_tx,)` | float32 | s | A/D start time per transmit |
+| `scan/t0_delays` | `(n_tx, n_el)` | float32 | s | Per-element transmit fire times |
+| `scan/tx_apodizations` | `(n_tx, n_el)` | float32 | - | Per-element transmit apodization |
+| `scan/focus_distances` | `(n_tx,)` | float32 | m | Focus distance per transmit (0 = plane wave) |
+| `scan/polar_angles` | `(n_tx,)` | float32 | rad | Transmit steering (polar) angle |
+| `scan/transmit_origins` | `(n_tx, 3)` | float32 | m | Transmit beam origin (x, y, z) |
+| `probe/probe_geometry` | `(n_el, 3)` | float32 | m | Element positions (x, y, z) |
+
+## Subject Metadata
+
+No human or animal subjects. Targets: hypoechoic/hyperechoic phantom inclusions. Scanner: Alpinion E-Cube 12R. Probe: L3-8 linear array (128 elements).
+
+## Data Validation
+
+A Delay-And-Sum `zea.Pipeline` is provided in the **`pipeline.yaml` at the submission root** and
+run by the single **`reconstruct.py` at the submission root**:
+`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`
+(RF is demodulated in-pipeline; IQ uses a baseband pipeline). The script is geometry-driven and
+recurses into every sub-dataset folder; running `python reconstruct.py` from the root reconstructs
+every `.hdf5` in the collection (or pass a folder-qualified path for a single acquisition) and writes
+`<name>_zea_bmode.png` next to each file as a portable check that the recorded geometry and timing
+are correct.
+
+The reference B-mode images committed alongside the data (`<name>_bmode.png`) are produced with the
+UltraSound ToolBox (USTB) MATLAB Delay-And-Sum beamformer — the exact per-dataset reconstruction
+used in the public USTB dataset catalog (https://unioslo.github.io/USTB/datasets.html), with
+scanline transmit apodization for focused/sector acquisitions and correct sector-scan geometry.
+These are the recommended reference reconstructions for visual verification.
+
+## Known Issues
+
+Single-frame acquisitions; two transmit schemes (FI, CPWC).
+
+## Ethical Considerations
+
+Phantom acquisitions; no human or animal subjects. No ethical considerations beyond standard laboratory practice.

oslo/E_simulation/README.md

@@ -0,0 +1,132 @@
+---
+pretty_name: "USTB - Simulation (Field II)"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - simulation
+  - field-ii
+  - synthetic
+size_categories:
+  - n<1K
+---
+
+# USTB - Simulation (Field II)
+
+Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** contributed to the
+[OpenH-RF](https://github.com/open-h/OpenH-RF) initiative. All acquisitions are stored in the
+*zea* HDF5 file format (zea_version 0.1.0) and contain raw pre-beamformed
+channel data (`/data/raw_data`).
+
+## Dataset Description
+
+Physics-based synthetic channel-capture data generated with the Field II ultrasound simulation framework. The collection covers point scatterers, cysts, speckle, dynamic-range targets and blocked-array (aperture-apodized) configurations, using linear (L7-4-like) and phased (P4-like) virtual probes with CPWC, FI and STA sequences. Because the scattering medium is fully defined, exact ground-truth scatterer positions and medium parameters are known. One numerical calibration acquisition (PICMUS_numerical_calib_v2) was created in collaboration with our group as part of the PICMUS effort; it is included here while the other PICMUS datasets are excluded (see Known Issues).
+
+## Dataset Contributors
+
+University of Oslo (UiO), Department of Informatics. Primary contact: Ole Marius Hoel Rindal (omrindal@ifi.uio.no). Team: Ole Marius Hoel Rindal, Yucel Karabiyik, Sven Peter Nasholm, Andreas Austeng.
+
+## Dataset Creation Date
+
+06/23/2026 (packaging date; original acquisitions/simulations were produced between 2016 and 2023).
+
+## License / Terms of Use
+
+Released under **Creative Commons Attribution 4.0 International (CC BY 4.0)** — see the `LICENCE`
+file at the submission root (this license is also declared in the YAML frontmatter above). The
+contributed data is cleared for this license. The UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo. Contributed to OpenH-RF. Zenodo record 20261898.
+
+## Intended Usage
+
+Generalized reconstruction, beamformer development and validation with known ground truth (RFP task 6.1); resolution/contrast/dynamic-range characterization; training/validation of learned reconstruction methods. (OpenH-RF RFP task 6.1 Generalized Reconstruction).
+
+## Dataset Characterization
+
+- **Data Collection Method:** synthetic
+- **Labeling Method:** Synthetic ground truth (known scatterer positions and medium parameters).
+- **Acquisition system:** probe(s) L7-4, P4-1;
+  element positions stored in `/probe/probe_geometry` (meters); center frequency, sampling
+  frequency and sound speed stored per acquisition in `/scan` (see per-sample feature table).
+
+## Dataset Format
+
+All acquisitions are stored in the **zea** HDF5 file format. Each `.hdf5` file is a single
+acquisition with raw channel data `/data/raw_data` of shape
+`(n_frames, n_tx, n_ax, n_el, n_ch)` and a fully populated `/scan` group describing the transmit
+sequence (delays, focus distances, steering angles, apodization, timing). Data type: RF/IQ (n_ch in [1, 2]).
+No demodulation or decimation was applied during packaging beyond conversion from the USTB
+Ultrasound File Format (UFF) to zea; RF data is demodulated inside the reconstruction pipeline.
+
+## Dataset Quantification
+
+- **Number of acquisitions:** 11
+- **Total channel-capture frames:** 17
+- **Train / validation / test split:** not predefined (research dataset).
+- **Total size on disk:** 3464 MB
+
+Per-acquisition summary:
+
+| Acquisition | frames | transmits | samples | elements | n_ch | fs (MHz) | fc (MHz) | size (MB) |
+|---|---|---|---|---|---|---|---|---|
+| `FieldII_CPWC_point_scatterers_res_v2` | 7 | 1 | 7792 | 128 | 1 | 100.0 | 5.16 | 2 |
+| `FieldII_CPWC_simulation_v2` | 1 | 1 | 6494 | 128 | 1 | 100.0 | 5.13 | 1 |
+| `FieldII_P4_point_scatterers` | 1 | 128 | 14349 | 64 | 1 | 100.0 | 2.56 | 471 |
+| `FieldII_speckle_DMASsimulation300000pts` | 1 | 96 | 10570 | 128 | 1 | 100.0 | 3.50 | 232 |
+| `FieldII_STAI_dynamic_range` | 1 | 128 | 7792 | 128 | 1 | 100.0 | 5.13 | 401 |
+| `FieldII_STAI_simulated_dynamic_range` | 1 | 128 | 7792 | 128 | 1 | 100.0 | 5.13 | 393 |
+| `FieldII_STAI_uniform_fov` | 1 | 128 | 2771 | 128 | 1 | 25.0 | 5.13 | 141 |
+| `PICMUS_numerical_calib_v2` | 1 | 5 | 445 | 128 | 2 | 5.2 | 5.21 | 2 |
+| `speckle_sim_FI_P4_probe_apod_1_speckle_long_many_angles` | 1 | 150 | 15786 | 64 | 1 | 100.0 | 2.56 | 607 |
+| `speckle_sim_FI_P4_probe_apod_2_speckle_long_many_angles` | 1 | 150 | 15786 | 64 | 1 | 100.0 | 2.56 | 607 |
+| `speckle_sim_FI_P4_probe_apod_3_speckle_long_many_angles` | 1 | 150 | 15786 | 64 | 1 | 100.0 | 2.56 | 607 |
+
+Per-sample feature table:
+
+| Field | Shape | Dtype | Units | Description |
+|---|---|---|---|---|
+| `data/raw_data` | `(n_frames, n_tx, n_ax, n_el, n_ch)` | float32 | a.u. | Raw pre-beamformed RF channel data |
+| `scan/sampling_frequency` | `scalar` | float32 | Hz | A/D sampling frequency |
+| `scan/center_frequency` | `scalar` | float32 | Hz | Transmit pulse center frequency |
+| `scan/demodulation_frequency` | `scalar` | float32 | Hz | Demodulation (carrier) frequency |
+| `scan/sound_speed` | `scalar` | float32 | m/s | Assumed medium speed of sound |
+| `scan/initial_times` | `(n_tx,)` | float32 | s | A/D start time per transmit |
+| `scan/t0_delays` | `(n_tx, n_el)` | float32 | s | Per-element transmit fire times |
+| `scan/tx_apodizations` | `(n_tx, n_el)` | float32 | - | Per-element transmit apodization |
+| `scan/focus_distances` | `(n_tx,)` | float32 | m | Focus distance per transmit (0 = plane wave) |
+| `scan/polar_angles` | `(n_tx,)` | float32 | rad | Transmit steering (polar) angle |
+| `scan/transmit_origins` | `(n_tx, 3)` | float32 | m | Transmit beam origin (x, y, z) |
+| `probe/probe_geometry` | `(n_el, 3)` | float32 | m | Element positions (x, y, z) |
+
+## Subject Metadata
+
+No human or animal subjects. Synthetic media simulated with Field II. Virtual probes: L7-4-like linear and P4-like phased arrays.
+
+## Data Validation
+
+A Delay-And-Sum `zea.Pipeline` is provided in the **`pipeline.yaml` at the submission root** and
+run by the single **`reconstruct.py` at the submission root**:
+`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`
+(RF is demodulated in-pipeline; IQ uses a baseband pipeline). The script is geometry-driven and
+recurses into every sub-dataset folder; running `python reconstruct.py` from the root reconstructs
+every `.hdf5` in the collection (or pass a folder-qualified path for a single acquisition) and writes
+`<name>_zea_bmode.png` next to each file as a portable check that the recorded geometry and timing
+are correct.
+
+The reference B-mode images committed alongside the data (`<name>_bmode.png`) are produced with the
+UltraSound ToolBox (USTB) MATLAB Delay-And-Sum beamformer — the exact per-dataset reconstruction
+used in the public USTB dataset catalog (https://unioslo.github.io/USTB/datasets.html), with
+scanline transmit apodization for focused/sector acquisitions and correct sector-scan geometry.
+These are the recommended reference reconstructions for visual verification.
+
+## Known Issues
+
+PICMUS calibration: 'PICMUS_numerical_calib_v2' was created in collaboration with our group as part of the PICMUS (Plane-wave Imaging Challenge in Medical UltraSound, IEEE IUS 2016) effort, and is therefore included here. The other PICMUS acquisitions (in-vivo carotid, experimental and simulated resolution/contrast) are deliberately excluded from this submission. Simulation framework: Field II (Jensen et al.).
+
+## Ethical Considerations
+
+Fully synthetic data generated with the Field II simulation framework; no human or animal subjects. No personal data is present. The included numerical calibration file was produced in collaboration with our group as part of the PICMUS effort (IEEE IUS 2016) and is released here under CC BY 4.0.

oslo/F_motion/README.md

@@ -0,0 +1,125 @@
+---
+pretty_name: "USTB - Motion Estimation (SWE / ARFI, Verasonics L7-4)"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - elastography
+  - shear-wave
+  - arfi
+size_categories:
+  - n<1K
+---
+
+# USTB - Motion Estimation (SWE / ARFI, Verasonics L7-4)
+
+Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** contributed to the
+[OpenH-RF](https://github.com/open-h/OpenH-RF) initiative. All acquisitions are stored in the
+*zea* HDF5 file format (zea_version 0.1.0) and contain raw pre-beamformed
+channel data (`/data/raw_data`).
+
+## Dataset Description
+
+Shear-wave elastography (SWE) and acoustic-radiation-force-impulse (ARFI) push-tracking phantom acquisitions on a Verasonics Vantage 256 with an L7-4 linear array. Each acquisition contains many high-frame-rate tracking frames following an acoustic push, suitable for tissue-motion and shear-wave-velocity estimation.
+
+## Dataset Contributors
+
+University of Oslo (UiO), Department of Informatics. Primary contact: Ole Marius Hoel Rindal (omrindal@ifi.uio.no). Team: Ole Marius Hoel Rindal, Yucel Karabiyik, Sven Peter Nasholm, Andreas Austeng.
+
+## Dataset Creation Date
+
+06/23/2026 (packaging date; original acquisitions/simulations were produced between 2016 and 2023).
+
+## License / Terms of Use
+
+Released under **Creative Commons Attribution 4.0 International (CC BY 4.0)** — see the `LICENCE`
+file at the submission root (this license is also declared in the YAML frontmatter above). The
+contributed data is cleared for this license. The UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo. Contributed to OpenH-RF. Zenodo record 20261898.
+
+## Intended Usage
+
+Motion estimation (RFP task 6.4): shear-wave velocity estimation, ARFI displacement tracking, and high-frame-rate motion reconstruction. (OpenH-RF RFP task 6.4 Motion Estimation).
+
+## Dataset Characterization
+
+- **Data Collection Method:** phantom
+- **Labeling Method:** Derived (elastography phantom of known/typical stiffness classes).
+- **Acquisition system:** probe(s) L7-4;
+  element positions stored in `/probe/probe_geometry` (meters); center frequency, sampling
+  frequency and sound speed stored per acquisition in `/scan` (see per-sample feature table).
+
+## Dataset Format
+
+All acquisitions are stored in the **zea** HDF5 file format. Each `.hdf5` file is a single
+acquisition with raw channel data `/data/raw_data` of shape
+`(n_frames, n_tx, n_ax, n_el, n_ch)` and a fully populated `/scan` group describing the transmit
+sequence (delays, focus distances, steering angles, apodization, timing). Data type: RF (n_ch=1).
+No demodulation or decimation was applied during packaging beyond conversion from the USTB
+Ultrasound File Format (UFF) to zea; RF data is demodulated inside the reconstruction pipeline.
+
+## Dataset Quantification
+
+- **Number of acquisitions:** 4
+- **Total channel-capture frames:** 800
+- **Train / validation / test split:** not predefined (research dataset).
+- **Total size on disk:** 473 MB
+
+Per-acquisition summary:
+
+| Acquisition | frames | transmits | samples | elements | n_ch | fs (MHz) | fc (MHz) | size (MB) |
+|---|---|---|---|---|---|---|---|---|
+| `ARFI_dataset` | 200 | 1 | 1664 | 128 | 1 | 20.8 | 5.21 | 170 |
+| `SWE_L7_type_I` | 200 | 1 | 1664 | 128 | 1 | 20.8 | 5.21 | 100 |
+| `SWE_L7_type_III` | 200 | 1 | 1664 | 128 | 1 | 20.8 | 5.21 | 102 |
+| `SWE_L7_type_IV` | 200 | 1 | 1664 | 128 | 1 | 20.8 | 5.21 | 101 |
+
+Per-sample feature table:
+
+| Field | Shape | Dtype | Units | Description |
+|---|---|---|---|---|
+| `data/raw_data` | `(n_frames, n_tx, n_ax, n_el, n_ch)` | float32 | a.u. | Raw pre-beamformed RF channel data |
+| `scan/sampling_frequency` | `scalar` | float32 | Hz | A/D sampling frequency |
+| `scan/center_frequency` | `scalar` | float32 | Hz | Transmit pulse center frequency |
+| `scan/demodulation_frequency` | `scalar` | float32 | Hz | Demodulation (carrier) frequency |
+| `scan/sound_speed` | `scalar` | float32 | m/s | Assumed medium speed of sound |
+| `scan/initial_times` | `(n_tx,)` | float32 | s | A/D start time per transmit |
+| `scan/t0_delays` | `(n_tx, n_el)` | float32 | s | Per-element transmit fire times |
+| `scan/tx_apodizations` | `(n_tx, n_el)` | float32 | - | Per-element transmit apodization |
+| `scan/focus_distances` | `(n_tx,)` | float32 | m | Focus distance per transmit (0 = plane wave) |
+| `scan/polar_angles` | `(n_tx,)` | float32 | rad | Transmit steering (polar) angle |
+| `scan/transmit_origins` | `(n_tx, 3)` | float32 | m | Transmit beam origin (x, y, z) |
+| `probe/probe_geometry` | `(n_el, 3)` | float32 | m | Element positions (x, y, z) |
+
+## Subject Metadata
+
+No human or animal subjects. Elastography phantoms. Scanner: Verasonics Vantage 256. Probe: L7-4 linear array (128 elements).
+
+## Data Validation
+
+A Delay-And-Sum `zea.Pipeline` is provided in the **`pipeline.yaml` at the submission root** and
+run by the single **`reconstruct.py` at the submission root**:
+`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`
+(RF is demodulated in-pipeline; IQ uses a baseband pipeline). The script is geometry-driven and
+recurses into every sub-dataset folder; running `python reconstruct.py` from the root reconstructs
+every `.hdf5` in the collection (or pass a folder-qualified path for a single acquisition) and writes
+`<name>_zea_bmode.png` next to each file as a portable check that the recorded geometry and timing
+are correct. These plane-wave tracking acquisitions use the non-focused `compound` pipeline, and the
+reference reconstruction shows a single tracking frame.
+
+The reference B-mode images committed alongside the data (`<name>_bmode.png`) are produced with the
+UltraSound ToolBox (USTB) MATLAB Delay-And-Sum beamformer — the exact per-dataset reconstruction
+used in the public USTB dataset catalog (https://unioslo.github.io/USTB/datasets.html). These are
+the recommended reference reconstructions for visual verification.
+
+## Known Issues
+
+Push-track sequences contain many frames at a high frame rate; the B-mode reference reconstruction shows a single tracking frame. Displacement/velocity estimation requires frame-to-frame processing not included in the reference pipeline. The displacement estimation as implemented in the UltraSound ToolBox (USTB) can be provided/added for these motion datasets on request if needed.
+
+## Ethical Considerations
+
+Phantom acquisitions; no human or animal subjects. No ethical considerations beyond standard laboratory practice.

oslo/README.md

@@ -0,0 +1,110 @@
+---
+pretty_name: "OpenH-RF — UltraSound ToolBox (USTB) Channel Capture Collection"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - beamforming
+  - channel-data
+size_categories:
+  - n<1K
+---
+
+# UltraSound ToolBox (USTB) Channel Capture Collection — OpenH-RF Submission
+
+Contributed by the **University of Oslo (UiO), Department of Informatics** (the USTB team)
+to the [OpenH-RF](https://github.com/open-h/OpenH-RF) initiative. All data is pre-beamformed
+(raw channel-capture) ultrasound stored in the **zea** HDF5 format (`zea_version 0.1.0`,
+≥ required `0.1.0a3`) and released under **CC BY 4.0**.
+
+## Contents
+
+39 acquisitions packaged into six application sub-datasets. Each sub-dataset folder contains its
+zea `.hdf5` files, a Hugging Face–style `README.md` data card, and one reference B-mode PNG per
+acquisition. The **`reconstruct.py`, `pipeline.yaml`, and the CC BY 4.0 `LICENCE` live once at the
+submission root** — the reconstruction reconstructs every sub-dataset (the pipeline is identical
+across folders), and the single LICENCE covers the whole collection (each data card also declares
+`license: cc-by-4.0` in its YAML frontmatter).
+
+| Folder | Sub-dataset | Tier | RFP task | Acq. |
+|---|---|---|---|---|
+| `A_cardiac/` | In-vivo cardiac (Verasonics P4-2) | in-vivo human (research) | 6.1 Generalized Reconstruction | 2 |
+| `B_carotid/` | In-vivo carotid (Verasonics L7-4) | in-vivo human (research) | 6.1 Generalized Reconstruction | 3 |
+| `C_verasonics_phantom/` | Phantom (Verasonics L7-4 / P4) | phantom | 6.1 Generalized Reconstruction | 15 |
+| `D_alpinion_phantom/` | Phantom (Alpinion L3-8) | phantom | 6.1 Generalized Reconstruction | 4 |
+| `E_simulation/` | Simulation (Field II) | simulation | 6.1 Generalized Reconstruction | 11 |
+| `F_motion/` | Motion estimation (SWE / ARFI, L7-4) | phantom | 6.4 Motion Estimation | 4 |
+
+Total: **39 acquisitions**, ~10 GB on disk.
+
+## How to reconstruct
+
+Every acquisition is reconstructable from the file alone — all acquisition parameters live in the
+zea `/scan` and `/probe` groups. A single `reconstruct.py` at the submission root reconstructs
+every acquisition in every sub-dataset folder:
+
+```bash
+export KERAS_BACKEND=jax
+python reconstruct.py                          # standard recon for every .hdf5
+python reconstruct.py --refocus                # also emit REFoCUS where enabled
+python reconstruct.py A_cardiac/<file>.hdf5    # a single acquisition
+```
+
+All reconstruction choices live in **`parameters.yaml`** — one entry per acquisition giving its
+`pipeline` (which `zea.Pipeline` to use), display window (`zlims`/`xlims` in mm) and `dynamic_range`.
+Every acquisition uses the same workflow (load parameters → run the pipeline → plot); there is no
+per-file logic in the script. Each `pipeline` value maps to a `zea.Pipeline` YAML at the root:
+
+| `pipeline` | Used for | `zea.Pipeline` |
+|---|---|---|
+| `scanline` | focused linear (FI) scans | `pipeline_scanline.yaml`: `beamform` on a `grid_type: scanline` grid with `enable_receive_apodization: true` — one focused transmit per image line. The artifact-free reconstruction for a walking-focus linear scan (compounding focused beams onto a shared grid leaves a band at the focal depth). |
+| `sector` | phased-array / steered focused sector scans | `pipeline_sector.yaml`: polar grid + scan conversion; pressure-field-weighted DAS with peaked weighting (≈ scanline) and `focal_region_length`. |
+| `iq` | baseband IQ (`n_ch == 2`, e.g. PICMUS) | `pipeline_iq.yaml` (no demodulation step). |
+| `compound` | non-focused linear (plane-wave / diverging / STA / SWE-ARFI) | `pipeline.yaml`: coherent compounding, no pfield (these insonify the whole field of view). |
+
+The pipelines share the same shape as zea's regular B-mode pipeline (`cast → apply_window →
+demodulate → beamform → envelope → normalize → log_compress`). Scanline imaging
+uses the same `beamform` op with a scanline grid plus receive apodization rather than a dedicated
+scanline-specific operation. Two zea features used in this submission are scanline receive
+apodization (`enable_receive_apodization`) and `focal_region_length` (focal-region delay blending,
+Rindal et al., IUS 2018).
+
+An acquisition may also set `refocus: true` in `parameters.yaml`. When `reconstruct.py` is run
+with the `--refocus` flag (off by default), it additionally runs a REFoCUS reconstruction for
+those acquisitions — transmit-encoding recovery (Bottenus, 2018) that
+inverts the transmit-encoding matrix to recover the multistatic (full-matrix-capture) dataset
+before pressure-field-weighted DAS — and writes a `<name>_zea_refocus_bmode.png` alongside the
+standard reconstruction. REFoCUS is enabled for **every acquisition with enough encoded transmits
+for the inversion to be well posed (≥ 8 transmit events)** — coherent plane-wave compounding
+(CPWC), diverging waves (DW), and focused linear (FI) and phased-array sector scans. Phased-array
+`sector` acquisitions use `pipeline_refocus_sector.yaml` (polar grid + scan conversion, preserving
+the sector geometry); every other geometry uses the linear/cartesian `pipeline_refocus.yaml`.
+REFoCUS is **not** enabled where the inversion is ill-posed or undefined: single/few-transmit
+acquisitions (the `n_tx = 1` plane-wave tracking sets and single-angle simulations, PICMUS's
+5-angle IQ) and synthetic transmit aperture (STA) acquisitions, which are already multistatic.
+
+## Reference images
+
+Each acquisition ships with:
+- `<name>_zea_bmode.png` — produced by the root `reconstruct.py` (zea); the reproducible reference.
+- `<name>_zea_bmode_old.png` — the initial v2 zea reconstruction (kept for comparison).
+- `<name>_bmode.png` — the canonical USTB MATLAB Delay-And-Sum reconstruction from the public
+  [USTB dataset catalog](https://unioslo.github.io/USTB/datasets.html), for cross-validation.
+- `<name>_zea_refocus_bmode.png` — REFoCUS variant, for acquisitions with `refocus: true`
+  (CPWC / DW / focused FI / sector with ≥ 8 transmits; not STA or single/few-transmit sets).
+
+## Licensing & attribution
+
+Released under **CC BY 4.0**. Please cite the UltraSound ToolBox (USTB), University of Oslo
+(Zenodo record 20261898). `PICMUS_numerical_calib_v2` (group E) was created **in collaboration
+with our group** as part of the PICMUS effort and is included on that basis; the other PICMUS
+datasets are excluded.
+
+## Contact
+
+Ole Marius Hoel Rindal — omrindal@ifi.uio.no (UiO, USTB).

oslo/pipeline.yaml

@@ -0,0 +1,30 @@
+# B-mode pipeline for non-focused linear-array acquisitions: plane-wave
+# compounding (CPWC), diverging waves (DW), synthetic transmit aperture (STA)
+# and plane-wave tracking (SWE/ARFI). These insonify the whole field of view,
+# so pressure-field weighting is disabled (equal coherent compounding).
+#
+# apply_window tapers/zeros the start of each RF line to suppress the transmit
+# near-field ringdown and receive sidelobes.
+
+parameters:
+  f_number: 1.75
+  grid_size_x: 400
+  grid_size_z: 600
+  dynamic_range: [-60, 0]
+  selected_transmits: all
+
+pipeline:
+  operations:
+    - name: keras.ops.cast
+      params:
+        dtype: float32
+    - name: apply_window
+    - name: demodulate
+    - name: beamform
+      params:
+        beamformer: delay_and_sum
+        enable_pfield: false
+        num_patches: 200
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress

oslo/pipeline_iq.yaml

@@ -0,0 +1,30 @@
+# B-mode pipeline for baseband IQ linear-array acquisitions (n_ch == 2).
+#
+# The data is already demodulated, so there is no demodulate step. These
+# acquisitions (e.g. PICMUS CPWC) are non-focused, so pressure-field weighting
+# is disabled.
+#
+# apply_window tapers/zeros the start of each RF line to suppress the transmit
+# near-field ringdown and receive sidelobes.
+
+parameters:
+  f_number: 1.75
+  grid_size_x: 400
+  grid_size_z: 600
+  dynamic_range: [-60, 0]
+  selected_transmits: all
+
+pipeline:
+  operations:
+    - name: keras.ops.cast
+      params:
+        dtype: float32
+    - name: apply_window
+    - name: beamform
+      params:
+        beamformer: delay_and_sum
+        enable_pfield: false
+        num_patches: 200
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress

oslo/pipeline_refocus.yaml

@@ -0,0 +1,43 @@
+# B-mode pipeline with REFoCUS transmit-encoding recovery, for non-focused
+# linear-array acquisitions that have many transmit events (e.g. CPWC / DW).
+#
+# REFoCUS (Bottenus 2018) inverts the transmit-encoding matrix in the frequency
+# domain to recover the multistatic (per-element / full-matrix-capture) dataset
+# from the encoded transmit sequence; that synthetic aperture is then beamformed
+# with pressure-field-weighted Delay-And-Sum. Compared with directly compounding
+# the encoded transmits (pipeline.yaml) this can sharpen lateral resolution and
+# contrast. The inversion needs enough transmit events to be well posed (>= 8),
+# so this pipeline is only applied to the many-angle acquisitions flagged with
+# `refocus: true` in parameters.yaml (the standard compound reconstruction is
+# still produced for those files as well).
+#
+# jit_compile is disabled on refocus to avoid a cuBLASLt autotuning failure on
+# the complex matmul under XLA on some GPUs.
+
+parameters:
+  f_number: 1.75
+  grid_size_x: 400
+  grid_size_z: 600
+  dynamic_range: [-60, 0]
+  selected_transmits: all
+
+pipeline:
+  operations:
+    - name: keras.ops.cast
+      params:
+        dtype: float32
+    - name: apply_window
+    - name: refocus
+      params:
+        method: adjoint
+        param: null
+        jit_compile: false
+    - name: demodulate
+    - name: beamform
+      params:
+        beamformer: delay_and_sum
+        enable_pfield: true
+        num_patches: 200
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress

oslo/pipeline_refocus_sector.yaml

@@ -0,0 +1,53 @@
+# REFoCUS transmit-encoding recovery for phased-array focused SECTOR scans.
+#
+# The sector counterpart of pipeline_refocus.yaml: REFoCUS (Bottenus 2018)
+# inverts the transmit-encoding matrix to recover the multistatic (full-matrix-
+# capture) dataset from the focused sector beams, which is then beamformed with
+# pressure-field-weighted Delay-And-Sum on a polar grid and scan-converted to
+# cartesian for display. Compared with pipeline_refocus.yaml (linear/cartesian)
+# this keeps the phased-array geometry: polar grid (angular limits auto-derived
+# from the transmit angles) and the full receive aperture (f_number 0), because
+# a finite f-number would reject the wide steering angles at the sector edges.
+#
+# Used for sector acquisitions flagged `refocus: true` in parameters.yaml. Like
+# the linear REFoCUS pipeline it needs enough transmit events to be well posed
+# (>= 8); the standard sector reconstruction (pipeline_sector.yaml) is still
+# produced for those files as well.
+#
+# The peaked pfield weighting / focal_region_length used in pipeline_sector.yaml
+# are dropped here: after REFoCUS the transmits are synthetic per-element events,
+# so the "dominant focused beam" weighting no longer applies (matches the plain
+# pfield DAS used in the linear REFoCUS pipeline).
+#
+# jit_compile is disabled on refocus to avoid a cuBLASLt autotuning failure on
+# the complex matmul under XLA on some GPUs.
+
+parameters:
+  f_number: 0
+  grid_type: polar
+  grid_size_x: 400
+  grid_size_z: 600
+  dynamic_range: [-60, 0]
+  selected_transmits: all
+
+pipeline:
+  operations:
+    - name: keras.ops.cast
+      params:
+        dtype: float32
+    - name: apply_window
+    - name: refocus
+      params:
+        method: adjoint
+        param: null
+        jit_compile: false
+    - name: demodulate
+    - name: beamform
+      params:
+        beamformer: delay_and_sum
+        enable_pfield: true
+        num_patches: 200
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress
+    - name: scan_convert

oslo/pipeline_scanline.yaml

@@ -0,0 +1,27 @@
+# Scanline (line-by-line) B-mode for focused linear (FI) scans: each focused
+# transmit forms one image line (no cross-transmit compounding).
+
+parameters:
+  f_number: 1.75
+  dynamic_range: [-60, 0]
+  enable_scanline: true
+  grid_type: cartesian
+  selected_transmits: all
+  grid_size_z: 700
+
+pipeline:
+  operations:
+    - name: keras.ops.cast
+      params:
+        dtype: float32
+    - name: apply_window
+    - name: demodulate
+    - name: beamform
+      params:
+        beamformer: delay_and_sum
+        enable_aligned_apodization: true
+        enable_pfield: false
+        num_patches: 200
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress

oslo/pipeline_sector.yaml

@@ -0,0 +1,44 @@
+# B-mode pipeline for phased-array focused sector scans.
+#
+# Beamformed on a polar grid (angular limits auto-derived from the transmit
+# angles) then scan-converted to cartesian for display. The full receive
+# aperture is used (f_number 0): a finite f-number mask is defined relative to
+# the vertical axis and would reject the wide steering angles at the sector edges.
+# Pressure-field weighting and focal-region smoothing are enabled (focused data);
+# pfield is peaked (see pfield_kwargs) to approximate per-beam scanline imaging.
+#
+# apply_window tapers/zeros the start of each RF line to suppress the transmit
+# near-field ringdown and receive sidelobes.
+
+parameters:
+  f_number: 0
+  grid_type: polar
+  grid_size_x: 400
+  grid_size_z: 600
+  dynamic_range: [-60, 0]
+  selected_transmits: all
+  focal_region_length: 0.002
+  pfield_kwargs:
+    interpolation: bilinear
+    # Peaked weighting (high alpha + percentile) concentrates each pixel on its
+    # dominant transmit beam, recovering the sharp specular structure of a dense
+    # focused sector that flat weighting would smooth away.
+    percentile: 70
+    alpha: 15
+
+pipeline:
+  operations:
+    - name: keras.ops.cast
+      params:
+        dtype: float32
+    - name: apply_window
+    - name: demodulate
+    - name: beamform
+      params:
+        beamformer: delay_and_sum
+        enable_pfield: true
+        num_patches: 200
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress
+    - name: scan_convert