Move the JHU Alpinion phantom data to jhu-pulselab/alpinion_phantom and credit JHU

.gitattributes

@@ -23491,3 +23491,11 @@ kaist-snubh-barreleye/data/S36_D1.hdf5 filter=lfs diff=lfs merge=lfs -text
 kaist-snubh-barreleye/data/S36_D2.hdf5 filter=lfs diff=lfs merge=lfs -text
 kaist-snubh-barreleye/data/S37_D1.hdf5 filter=lfs diff=lfs merge=lfs -text
 kaist-snubh-barreleye/data/S37_D2.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/D_alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/D_alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/D_alpinion_phantom/JHU_Alpinion_L3-8_FI_hyperechoic_scatterers.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/D_alpinion_phantom/JHU_Alpinion_L3-8_FI_hypoechoic.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hyperechoic_scatterers.hdf5 filter=lfs diff=lfs merge=lfs -text
+jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hypoechoic.hdf5 filter=lfs diff=lfs merge=lfs -text

jhu-pulselab/README.md

@@ -0,0 +1,69 @@
+---
+name: jhu-pulselab
+pretty_name: "UltraSound ToolBox (USTB) Channel Capture Data, PULSE Lab, Johns Hopkins University"
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+language:
+  - en
+tags:
+  - ultrasound
+  - rf
+  - open-h-rf
+  - beamforming
+  - channel-data
+size_categories:
+  - n<1K
+---
+
+# UltraSound ToolBox (USTB) Channel Capture Data, PULSE Lab, Johns Hopkins University
+
+![B-modes of all four acquisitions: plane-wave and focused imaging of a hypoechoic cyst and of hyperechoic scatterers](assets/hero.png)
+
+*First frames of all four acquisitions, reconstructed from the raw channel data with `reconstruct.py`. Top: [`alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic.hdf5), [`alpinion_phantom/JHU_Alpinion_L3-8_FI_hypoechoic`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hypoechoic.hdf5). Bottom: [`alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers.hdf5), [`alpinion_phantom/JHU_Alpinion_L3-8_FI_hyperechoic_scatterers`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hyperechoic_scatterers.hdf5). Panels are scaled to a common height per row, not to a common physical scale.*
+
+## Dataset Description
+
+Contributed by the **Photoacoustic & Ultrasonic Systems Engineering (PULSE) Lab, Johns Hopkins University (JHU)** to the [Open-H-RF](https://github.com/open-h/Open-H-RF) initiative. The data is owned by JHU. All data is pre-beamformed (raw channel-capture) ultrasound stored in the **zea** HDF5 format and released under **CC BY 4.0**.
+
+These acquisitions are part of the **UltraSound ToolBox (USTB) Channel Capture Collection**; the rest of that collection is in [`oslo/`](../oslo/README.md).
+
+4 acquisitions packaged into a single application sub-dataset. The sub-dataset folder contains its zea `.hdf5` files, a Hugging Face–style `README.md` data card, and reference B-mode images. The **`reconstruct.py`, `parameters.yaml` and `pipeline*.yaml` files live once at the root of this collection** (`jhu-pulselab/`); the sub-dataset folder also holds a `pipeline.yaml` for its example acquisition. The data card declares `license: cc-by-4.0` in its YAML frontmatter.
+
+| Folder | Sub-dataset | Tier | RFP task | Acq. |
+|---|---|---|---|---|
+| [`alpinion_phantom/`](alpinion_phantom/README.md) | Phantom (Alpinion L3-8) | phantom | 6.1 Generalized Reconstruction | 4 |
+
+Total: **4 acquisitions**, 0.47 GB of stored HDF5 data.
+
+## Dataset Contributor(s)
+
+- Muyinatu A. Lediju Bell <mledijubell@jhu.edu> (primary contact)
+- Ole Marius Hoel Rindal <omrindal@ifi.uio.no>
+- Photoacoustic & Ultrasonic Systems Engineering (PULSE) Lab, Johns Hopkins University
+
+## Dataset Creation Date
+
+06/23/2026 (packaging date; the original acquisitions were made at the PULSE Lab, Johns Hopkins University, in 2017).
+
+## License / Terms of Use
+
+[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.
+
+## Processing the Dataset
+
+Every acquisition is reconstructable from the file alone — all acquisition parameters live in the zea `/scan` and `/probe` groups. The acquisitions can be processed with the `reconstruct.py` [script](https://github.com/open-h/Open-H-RF/blob/main/datasets/jhu-pulselab/reconstruct.py), as provided in the [Open-H-RF GitHub repository](https://github.com/open-h/Open-H-RF), together with the `pipeline*.yaml` and `parameters.yaml` definitions in this folder and the [zea library](https://github.com/tue-bmd/zea). The script streams the data from the Hugging Face Hub: set `PATHS` to the acquisition to reconstruct and `REFOCUS = True` to also emit the REFoCUS variant (the script and pipelines are the same as the USTB collection's; see its card's [Reconstruction Details](../oslo/README.md#reconstruction-details)). The sub-dataset folder also holds a `pipeline.yaml` for its example acquisition, so it can be rendered with a single `zea process` command (see the [sub-dataset card](alpinion_phantom/README.md)).
+
+## Dataset Format
+
+[zea v0.1.6](https://github.com/tue-bmd/zea)
+
+## Dataset Quantification
+
+**Current Open-H-RF release:** 4 HDF5 files; 466.42 MB (466,419,712 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.
+
+## Citation
+
+Please credit the PULSE Lab, Johns Hopkins University, as the owner of this data, and cite the UltraSound ToolBox (USTB) proceedings paper:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)

oslo/D_alpinion_phantom/Alpinion_L3-8_CPWC_hyperechoic_scatterers.hdf5 → jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers.hdf5

@@ -1,3 +1,3 @@
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+oid sha256:1fb6ea2449dc40ffc0f7ae355f525788025fa519648455df8cc64f756d110831
 size 40894464

oslo/D_alpinion_phantom/Alpinion_L3-8_CPWC_hypoechoic.hdf5 → jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic.hdf5

@@ -1,3 +1,3 @@
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 size 40960000

oslo/D_alpinion_phantom/Alpinion_L3-8_FI_hyperechoic_scatterers.hdf5 → jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hyperechoic_scatterers.hdf5

@@ -1,3 +1,3 @@
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 size 192348160

oslo/D_alpinion_phantom/Alpinion_L3-8_FI_hypoechoic.hdf5 → jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hypoechoic.hdf5

@@ -1,3 +1,3 @@
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 size 192217088

{oslo/D_alpinion_phantom → jhu-pulselab/alpinion_phantom}/README.md

@@ -1,6 +1,6 @@
 ---
-name: oslo-d-alpinion-phantom
-pretty_name: "USTB - Phantom (Alpinion L3-8)"
+name: jhu-pulselab-alpinion-phantom
+pretty_name: "USTB - Phantom (Alpinion L3-8, PULSE Lab, Johns Hopkins University)"
 license: cc-by-4.0
 task_categories:
   - image-to-image
@@ -12,37 +12,40 @@ tags:
   - open-h-rf
   - phantom
   - alpinion
+  - ustb
 size_categories:
   - n<1K
 ---
 
-# USTB - Phantom (Alpinion L3-8)
+# USTB - Phantom (Alpinion L3-8, PULSE Lab, Johns Hopkins University)
 
-![Plane-wave compounded B-mode of hypoechoic cysts](assets/hero.png)
+![B-modes of all four acquisitions: plane-wave and focused imaging of a hypoechoic cyst and of hyperechoic scatterers](assets/hero.png)
 
-*First frame of [`Alpinion_L3-8_CPWC_hypoechoic.hdf5`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/D_alpinion_phantom/Alpinion_L3-8_CPWC_hypoechoic.hdf5), reconstructed from the raw channel data with `reconstruct.py`.*
+*First frames of all four acquisitions, reconstructed from the raw channel data with `reconstruct.py`. Top: [`JHU_Alpinion_L3-8_CPWC_hypoechoic`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic.hdf5), [`JHU_Alpinion_L3-8_FI_hypoechoic`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hypoechoic.hdf5). Bottom: [`JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers.hdf5), [`JHU_Alpinion_L3-8_FI_hyperechoic_scatterers`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_FI_hyperechoic_scatterers.hdf5). Panels are scaled to a common height per row, not to a common physical scale.*
 
 ## Dataset Description
 
-Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** (see the [collection card](../README.md)).
+Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** (see the [PULSE Lab collection card](../README.md) and the [USTB collection card](../../oslo/README.md)).
 
-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.
+**Data owner: Johns Hopkins University (JHU).** The data were acquired by Muyinatu A. Lediju Bell and Ole Marius Hoel Rindal at the Photoacoustic & Ultrasonic Systems Engineering (PULSE) Lab, JHU, on the PULSE Lab's Alpinion E-Cube 12R research scanner.
+
+Phantom channel-capture data of a CIRS General Purpose Ultrasound Phantom, acquired with an L3-8 linear-array probe. Hypoechoic and hyperechoic targets imaged with focused (FI) and coherent plane-wave compounding (CPWC) sequences.
+
+These recordings have been publicly available through the UltraSound ToolBox (USTB) since 2017, with M. A. Lediju Bell and O. M. H. Rindal as authors. The University of Oslo (UiO) converted the data to the zea format and prepared it for Open-H-RF. Open-H-RF `v1.0` published these four acquisitions as `oslo/D_alpinion_phantom/`; they now live under `jhu-pulselab/`, and each file credits JHU in its `/metadata/credit` and `description` fields.
 
 ## Dataset Contributor(s)
 
-- Ole Marius Hoel Rindal <omrindal@ifi.uio.no> (primary contact)
-- Yucel Karabiyik
-- Sven Peter Nasholm
-- Andreas Austeng
-- University of Oslo (UiO), Department of Informatics
+- Johns Hopkins University (JHU), data owner
+- Muyinatu A. Lediju Bell <mledijubell@jhu.edu>, PULSE Lab, JHU (primary contact)
+- Ole Marius Hoel Rindal <omrindal@ifi.uio.no>, University of Oslo (UiO), Department of Informatics (data acquisition at the PULSE Lab; zea conversion)
 
 ## Dataset Creation Date
 
-06/23/2026 (packaging date; original acquisitions/simulations were produced between 2016 and 2023).
+Acquired at the PULSE Lab, JHU, in 2017. Packaged in zea format on 06/23/2026.
 
 ## License / Terms of Use
 
-[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.
+[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. This data was first released with the USTB proceedings paper (Rodriguez-Molares et al., *The UltraSound ToolBox*, IEEE IUS 2017, doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)). Attribution under CC BY 4.0 means crediting the PULSE Lab, Johns Hopkins University, and citing the above paper (see [Citation](#citation)).
 
 ## Intended Usage
 
@@ -62,11 +65,11 @@ The example acquisition can be processed with the `pipeline.yaml` definition in
 
 ```bash
 zea process \
-  --dataset hf://nvidia/Open-H-RF/oslo/D_alpinion_phantom/Alpinion_L3-8_CPWC_hypoechoic.hdf5 \
-  --config hf://nvidia/Open-H-RF/oslo/D_alpinion_phantom/pipeline.yaml
+  --dataset hf://nvidia/Open-H-RF/jhu-pulselab/alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic.hdf5 \
+  --config hf://nvidia/Open-H-RF/jhu-pulselab/alpinion_phantom/pipeline.yaml
 ```
 
-This `pipeline.yaml` holds the pipeline and display window of that acquisition. Alternatively, all acquisitions can be processed with the `reconstruct.py` [script](https://github.com/open-h/Open-H-RF/blob/main/datasets/oslo/reconstruct.py) at the root of this collection, as provided in the [Open-H-RF GitHub repository](https://github.com/open-h/Open-H-RF), together with the `pipeline*.yaml` definitions at the collection root and the [zea library](https://github.com/tue-bmd/zea). The script streams the data from the Hugging Face Hub; `parameters.yaml` picks the pipeline, display window and dynamic range per acquisition (see the [collection card](../README.md#processing-the-dataset)).
+This `pipeline.yaml` holds the pipeline and display window of that acquisition. Alternatively, all acquisitions can be processed with the `reconstruct.py` [script](https://github.com/open-h/Open-H-RF/blob/main/datasets/jhu-pulselab/reconstruct.py) at the root of this collection (`jhu-pulselab/`), as provided in the [Open-H-RF GitHub repository](https://github.com/open-h/Open-H-RF), together with the `pipeline*.yaml` and `parameters.yaml` definitions there and the [zea library](https://github.com/tue-bmd/zea). The script streams the data from the Hugging Face Hub (see the [PULSE Lab collection card](../README.md#processing-the-dataset)).
 
 ## Dataset Format
 
@@ -87,10 +90,10 @@ 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 | 40.89 |
-| `Alpinion_L3-8_CPWC_hypoechoic` | 1 | 21 | 4352 | 128 | 1 | 40.0 | 6.00 | 40.96 |
-| `Alpinion_L3-8_FI_hyperechoic_scatterers` | 1 | 256 | 3474 | 128 | 1 | 40.0 | 6.00 | 192.35 |
-| `Alpinion_L3-8_FI_hypoechoic` | 1 | 256 | 3474 | 128 | 1 | 40.0 | 6.00 | 192.22 |
+| `JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers` | 1 | 21 | 4352 | 128 | 1 | 40.0 | 6.00 | 40.89 |
+| `JHU_Alpinion_L3-8_CPWC_hypoechoic` | 1 | 21 | 4352 | 128 | 1 | 40.0 | 6.00 | 40.96 |
+| `JHU_Alpinion_L3-8_FI_hyperechoic_scatterers` | 1 | 256 | 3474 | 128 | 1 | 40.0 | 6.00 | 192.35 |
+| `JHU_Alpinion_L3-8_FI_hypoechoic` | 1 | 256 | 3474 | 128 | 1 | 40.0 | 6.00 | 192.22 |
 
 Per-sample feature table:
 
@@ -108,20 +111,19 @@ Per-sample feature table:
 | `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) |
+| `metadata/credit` | `scalar` | string | - | Attribution: "Acquired by M. A. Lediju Bell and O. M. H. Rindal at the PULSE Lab, Johns Hopkins University (JHU). Owned by JHU." |
 
 ## Subject Metadata
 
-No human or animal subjects. Targets: hypoechoic/hyperechoic phantom inclusions. Scanner: Alpinion E-Cube 12R. Probe: L3-8 linear array (128 elements).
+No human or animal subjects. Targets: hypoechoic/hyperechoic inclusions and point scatterers in a CIRS General Purpose Ultrasound Phantom. Scanner: Alpinion E-Cube 12R (PULSE Lab, JHU). Probe: L3-8 linear array (128 elements).
 
 ## Data Validation
 
-A Delay-And-Sum `zea.Pipeline` (`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`; RF is demodulated in-pipeline, IQ uses a baseband pipeline) reconstructs every acquisition as a portable check that the recorded geometry and timing are correct (see *Processing the Dataset*).
-
-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.
+A Delay-And-Sum `zea.Pipeline` (`cast -> demodulate -> delay-and-sum beamform -> envelope detect -> normalize -> log compress`) reconstructs every acquisition as a portable check that the recorded geometry and timing are correct (see [Processing the Dataset](#processing-the-dataset)).
 
 ## Known Issues
 
-Single-frame acquisitions; two transmit schemes (FI, CPWC).
+Mixed transmit schemes across files (CPWC / FI).
 
 ## Ethical Considerations
 
@@ -129,4 +131,6 @@ Phantom acquisitions; no human or animal subjects. No ethical considerations bey
 
 ## Citation
 
-Please cite the UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo (Zenodo record 20261898).
+Please credit the PULSE Lab, Johns Hopkins University, as the owner of this data, and cite:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)

{oslo/D_alpinion_phantom → jhu-pulselab/alpinion_phantom}/pipeline.yaml

@@ -1,4 +1,4 @@
-# zea pipeline for D_alpinion_phantom/Alpinion_L3-8_CPWC_hypoechoic.hdf5, the example acquisition of this sub-dataset.
+# zea pipeline for alpinion_phantom/JHU_Alpinion_L3-8_CPWC_hypoechoic.hdf5, the example acquisition of this sub-dataset.
 # The shared ../pipeline.yaml plus the per-acquisition settings that
 # ../reconstruct.py takes from ../parameters.yaml (display window in metres,
 # dynamic range), so `zea process` renders it standalone.

jhu-pulselab/parameters.yaml

@@ -0,0 +1,32 @@
+# Per-acquisition reconstruction parameters, used by reconstruct.py. For each acquisition:
+#   pipeline      -- which reconstruction to use:
+#                    scanline (focused linear FI, per-beam, pipeline_scanline.yaml),
+#                    compound (plane-wave CPWC, pipeline.yaml).
+#   zlims/xlims   -- display window in mm (framing only).
+#   dynamic_range -- display dynamic range in dB (default [-60, 0]).
+#   refocus       -- if true, also emit a REFoCUS variant (<name>_zea_refocus_bmode.png,
+#                    pipeline_refocus.yaml). REFoCUS (Bottenus 2018) inverts the
+#                    transmit-encoding matrix to recover the multistatic dataset before DAS.
+
+# alpinion_phantom
+JHU_Alpinion_L3-8_CPWC_hyperechoic_scatterers:
+  pipeline: compound
+  refocus: true
+  zlims: [3, 55]
+  xlims: [-19, 19]
+JHU_Alpinion_L3-8_CPWC_hypoechoic:
+  pipeline: compound
+  refocus: true
+  zlims: [5, 50]
+  xlims: [-19, 19]
+JHU_Alpinion_L3-8_FI_hyperechoic_scatterers:
+  pipeline: scanline
+  refocus: true
+  zlims: [3, 55]
+  xlims: [-19, 19]
+JHU_Alpinion_L3-8_FI_hypoechoic:
+  pipeline: scanline
+  refocus: true
+  zlims: [0, 60]
+  xlims: [-19, 19]
+  dynamic_range: [-50, 0]

jhu-pulselab/pipeline.yaml

@@ -0,0 +1,28 @@
+# B-mode pipeline for the plane-wave compounding (CPWC) acquisitions. Plane
+# waves 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
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress

jhu-pulselab/pipeline_refocus.yaml

@@ -0,0 +1,42 @@
+# B-mode pipeline with REFoCUS transmit-encoding recovery, for non-focused
+# linear-array acquisitions that have many transmit events (CPWC and focused FI).
+#
+# 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
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress

jhu-pulselab/pipeline_scanline.yaml

@@ -0,0 +1,26 @@
+# 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
+    - name: envelope_detect
+    - name: normalize
+    - name: log_compress

oslo/A_cardiac/README.md

@@ -127,4 +127,6 @@ In-vivo data recorded from healthy adult volunteers at the University of Oslo wi
 
 ## Citation
 
-Please cite the UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo (Zenodo record 20261898).
+Please cite the UltraSound ToolBox (USTB) proceedings paper:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)

oslo/B_carotid/README.md

@@ -129,4 +129,6 @@ In-vivo data recorded from healthy adult volunteers at the University of Oslo wi
 
 ## Citation
 
-Please cite the UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo (Zenodo record 20261898).
+Please cite the UltraSound ToolBox (USTB) proceedings paper:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)

oslo/C_verasonics_phantom/README.md

@@ -140,4 +140,6 @@ Phantom / table-top acquisitions; no human or animal subjects are involved. No e
 
 ## Citation
 
-Please cite the UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo (Zenodo record 20261898).
+Please cite the UltraSound ToolBox (USTB) proceedings paper:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)

oslo/E_simulation/README.md

@@ -27,7 +27,7 @@ size_categories:
 
 Part of the **UltraSound ToolBox (USTB) Channel Capture Collection** (see the [collection card](../README.md)).
 
-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).
+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 on that basis.
 
 ## Dataset Contributor(s)
 
@@ -129,7 +129,7 @@ The reference B-mode images committed alongside the data (`<name>_bmode.png`) ar
 
 ## 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.).
+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. Simulation framework: Field II (Jensen et al.).
 
 ## Ethical Considerations
 
@@ -137,4 +137,6 @@ Fully synthetic data generated with the Field II simulation framework; no human
 
 ## Citation
 
-Please cite the UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo (Zenodo record 20261898).
+Please cite the UltraSound ToolBox (USTB) proceedings paper:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)

oslo/F_motion/README.md

@@ -130,4 +130,6 @@ Phantom acquisitions; no human or animal subjects. No ethical considerations bey
 
 ## Citation
 
-Please cite the UltraSound ToolBox (USTB) Channel Capture Collection, University of Oslo (Zenodo record 20261898).
+Please cite the UltraSound ToolBox (USTB) proceedings paper:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)

oslo/README.md

@@ -18,26 +18,25 @@ size_categories:
 
 # UltraSound ToolBox (USTB) Channel Capture Collection
 
-![B-modes from five of the six sub-datasets: in-vivo cardiac, in-vivo carotid, Verasonics and Alpinion phantoms, and simulation](assets/hero.png)
+![B-modes from four of the five sub-datasets: in-vivo cardiac, in-vivo carotid, Verasonics phantoms, and simulation](assets/hero.png)
 
-*First frames reconstructed from the raw channel data with `reconstruct.py`. Top: [`A_cardiac/Verasonics_P2-4_parasternal_long_subject_1`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/A_cardiac/Verasonics_P2-4_parasternal_long_subject_1.hdf5), [`A_cardiac/Verasonics_P2-4_apical_four_chamber_subject_1`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/A_cardiac/Verasonics_P2-4_apical_four_chamber_subject_1.hdf5), [`C_verasonics_phantom/FI_P4_cysts_center`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/C_verasonics_phantom/FI_P4_cysts_center.hdf5). Bottom: [`B_carotid/L7_FI_carotid_cross_1`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/B_carotid/L7_FI_carotid_cross_1.hdf5), [`C_verasonics_phantom/L7_FI_Verasonics_CIRS`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/C_verasonics_phantom/L7_FI_Verasonics_CIRS.hdf5), [`D_alpinion_phantom/Alpinion_L3-8_CPWC_hypoechoic`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/D_alpinion_phantom/Alpinion_L3-8_CPWC_hypoechoic.hdf5), [`E_simulation/PICMUS_numerical_calib_v2`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/E_simulation/PICMUS_numerical_calib_v2.hdf5). Panels are scaled to a common height per row, not to a common physical scale.*
+*First frames reconstructed from the raw channel data with `reconstruct.py`. Top: [`A_cardiac/Verasonics_P2-4_parasternal_long_subject_1`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/A_cardiac/Verasonics_P2-4_parasternal_long_subject_1.hdf5), [`A_cardiac/Verasonics_P2-4_apical_four_chamber_subject_1`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/A_cardiac/Verasonics_P2-4_apical_four_chamber_subject_1.hdf5), [`C_verasonics_phantom/FI_P4_cysts_center`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/C_verasonics_phantom/FI_P4_cysts_center.hdf5). Bottom: [`B_carotid/L7_FI_carotid_cross_1`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/B_carotid/L7_FI_carotid_cross_1.hdf5), [`C_verasonics_phantom/L7_FI_Verasonics_CIRS`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/C_verasonics_phantom/L7_FI_Verasonics_CIRS.hdf5), [`E_simulation/PICMUS_numerical_calib_v2`](https://huggingface.co/datasets/nvidia/Open-H-RF/blob/main/oslo/E_simulation/PICMUS_numerical_calib_v2.hdf5). Panels are scaled to a common height per row, not to a common physical scale.*
 
 ## Dataset Description
 
 Contributed by the **University of Oslo (UiO), Department of Informatics** (the USTB team) to the [Open-H-RF](https://github.com/open-h/Open-H-RF) initiative. All data is pre-beamformed (raw channel-capture) ultrasound stored in the **zea** HDF5 format and released under **CC BY 4.0**.
 
-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).
+35 acquisitions packaged into five 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). See [`jhu-pulselab/alpinion_phantom`](../jhu-pulselab/alpinion_phantom/README.md) to access additional data from this USTB Channel Capture Collection.
 
 | 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**, 8.61 GB of stored HDF5 data.
+Total: **35 acquisitions**, 8.15 GB of stored HDF5 data.
 
 ## Dataset Contributor(s)
 
@@ -65,7 +64,7 @@ Every acquisition is reconstructable from the file alone — all acquisition par
 
 ## Dataset Quantification
 
-**Current Open-H-RF release:** 39 HDF5 files; 8.61 GB (8,613,593,088 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.
+**Current Open-H-RF release:** 35 HDF5 files; 8.15 GB (8,147,173,376 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.
 
 ## Reconstruction Details
 
@@ -92,4 +91,8 @@ Each acquisition ships with:
 
 ## Citation
 
-Please cite the UltraSound ToolBox (USTB) Channel Capture Collection, 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.
+Please cite the UltraSound ToolBox (USTB) proceedings paper:
+
+A. Rodriguez-Molares, O. M. H. Rindal, O. Bernard, A. Nair, M. A. Lediju Bell, H. Liebgott, A. Austeng and L. Løvstakken, "The UltraSound ToolBox," in *2017 IEEE International Ultrasonics Symposium (IUS)*, 2017, pp. 1–4. doi:[10.1109/ULTSYM.2017.8092389](https://doi.org/10.1109/ULTSYM.2017.8092389)
+
+`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 seemingly missing group D, the Alpinion phantom data, is now [`jhu-pulselab/alpinion_phantom`](../jhu-pulselab/alpinion_phantom/README.md).

oslo/parameters.yaml

@@ -121,29 +121,6 @@ experimental_dynamic_range_phantom:
   zlims: [3, 58]
   xlims: [-19, 19]
 
-# D_alpinion_phantom
-Alpinion_L3-8_CPWC_hyperechoic_scatterers:
-  pipeline: compound
-  refocus: true
-  zlims: [3, 55]
-  xlims: [-19, 19]
-Alpinion_L3-8_CPWC_hypoechoic:
-  pipeline: compound
-  refocus: true
-  zlims: [5, 50]
-  xlims: [-19, 19]
-Alpinion_L3-8_FI_hyperechoic_scatterers:
-  pipeline: scanline
-  refocus: true
-  zlims: [3, 55]
-  xlims: [-19, 19]
-Alpinion_L3-8_FI_hypoechoic:
-  pipeline: scanline
-  refocus: true
-  zlims: [0, 60]
-  xlims: [-19, 19]
-  dynamic_range: [-50, 0]
-
 # E_simulation
 # Single plane wave (n_tx=1) -> REFoCUS N/A
 FieldII_CPWC_point_scatterers_res_v2: