weillcornell: tidy the data card, fix the hero sample name

weillcornell/README.md

@@ -20,13 +20,13 @@ size_categories:
 
 # Weill Cornell QUS Phantom Dataset
 
-![Reference zea reconstruction of ac1_15m_SK frame 0](assets/ac1_15m_SK_pipeline.png)
+![Reference zea reconstruction of ac10_15m_SK frame 0](assets/ac10_15m_SK_pipeline.png)
 
-*B-mode of frame 0 of [`data/ac1_15m_SK.hdf5`](https://huggingface.co/datasets/nvidia/OpenH-RF/blob/main/weillcornell/data/ac1_15m_SK.hdf5), reconstructed from the raw RF on the common 597 x 300 zea grid (approximately 3-25 mm depth).*
+*B-mode of frame 0 of [`data/ac10_15m_SK.hdf5`](https://huggingface.co/datasets/nvidia/OpenH-RF/blob/main/weillcornell/data/ac10_15m_SK.hdf5), reconstructed from the raw RF on the common 597 x 300 grid (approximately 3-25 mm depth).*
 
 ## Dataset Description
 
-Pre-beamformed RF channel data from three homogeneous tissue-mimicking phantoms. Each zea HDF5 acquisition is self-contained and includes raw RF, model-derived theoretical backscatter coefficient (BSC), direct per-frame Nakagami maps, and 20-frame pooled Nakagami references.
+Pre-beamformed RF channel data from three homogeneous tissue-mimicking phantoms, acquired for quantitative ultrasound (QUS). Next to the raw RF, each acquisition carries the phantom's model-derived theoretical backscatter coefficient (BSC), direct per-frame Nakagami maps, and 20-frame pooled Nakagami references, so single-frame QUS estimators can be trained and evaluated against targets stored in the same file.
 
 ## Dataset Contributor(s)
 
@@ -52,71 +52,61 @@ Not specified by the contributors.
 
 For Nakagami predictions, report MAE/RMSE and map correlation against the pooled reference. For BSC predictions, report the frequency range and unit and state whether evaluation uses linear BSC or a specified dB conversion.
 
-All QUS maps are public reference targets, not hidden competition labels.
-
 ## Dataset Characterization
 
-- Verasonics Vantage 256 and GE9LD linear array
-- 192 elements, 0.23 mm pitch, 5.2083 MHz center frequency
-- One normal-incidence plane wave per frame
-- 20.8333 MHz RF sampling; 1540 m/s sound-speed metadata
-- 3 phantoms x 2 operators x 20 probe placements x 20 frames
-- 120 acquisitions and 2400 frames
-- Phantom-only data; no human or animal subjects, clinical metadata, or PHI
-- No predefined train/validation/test split
-
-Keep all frames from one acquisition in the same split.
+- **Data collection method:** phantom — three homogeneous tissue-mimicking phantoms (`15m`, `18m`, `60m`), each scanned by two operators (`SK`, `TP`) at 20 probe placements
+- **Labeling method:** derived — BSC from the phantom material model; Nakagami maps estimated from the RF
+- **Acquisition system:** Verasonics Vantage 256, GE9LD linear array, 192 elements, 0.23 mm pitch, 5.2083 MHz center frequency, 20.8333 MHz RF sampling
+- **Transmit sequence:** one normal-incidence plane wave per frame; 1540 m/s sound speed
 
 ## Processing the Dataset
 
-The acquisitions can be processed with the `reconstruct.py` [script](https://github.com/open-h/OpenH-RF/blob/main/datasets/weillcornell/reconstruct.py) as provided in the [OpenH-RF GitHub repository](https://github.com/open-h/OpenH-RF), together with the `pipeline.yaml` definition in this folder and the [zea library](https://github.com/tue-bmd/zea). The script streams the data from the Hugging Face Hub.
+The acquisitions can be processed with the `pipeline.yaml` definition in this folder and the [zea library](https://github.com/tue-bmd/zea).
 
-Use an OpenH-RF environment with `zea==0.1.6` and a supported Keras backend, and set `ZEA_FILE` and `FRAME` at the top of the script to pick an acquisition. The script defines the pipeline in code, writes `pipeline.yaml`, saves the B-mode PNG, then prints the selected frame's RF shape, BSC band and unit, QUS map shapes, and direct per-frame-to-pooled Nakagami errors.
+`zea` streams the data from the Hugging Face Hub and processes it according to the pipeline. You can try it out with the following command:
 
-## Dataset Format
+```bash
+zea process \
+  --dataset hf://nvidia/OpenH-RF/weillcornell/data/ac10_15m_SK.hdf5 \
+  --config hf://nvidia/OpenH-RF/weillcornell/pipeline.yaml
+```
 
-[zea v0.1.6](https://github.com/tue-bmd/zea)
+Alternatively, you can use the `reconstruct.py` [script](https://github.com/open-h/OpenH-RF/blob/main/datasets/weillcornell/reconstruct.py) as provided in the [OpenH-RF GitHub repository](https://github.com/open-h/OpenH-RF). Besides the B-mode, it prints the selected frame's BSC band and unit, the QUS map shapes, and the error of the direct per-frame Nakagami maps against the pooled references.
 
-Each file follows zea 0.1.6 and contains one track. Raw RF is stored as `int16` ADC counts without demodulation, decimation, or resampling.
+## Dataset Format
 
-| Field under `tracks/track_0/data/` | Shape | dtype | Unit | Meaning |
-|---|---|---|---|---|
-| `raw_data` | `(20,1,n_ax,192,1)` | `int16` | ADC counts | Raw RF input |
-| `theoretical_bsc/values` | `(20,z,x,157)` | `float32` | `m^-1 sr^-1` | Model-derived BSC target |
-| `nakagami_m_per_frame/values` | `(20,z,x)` | `float32` | `1` | Direct single-frame shape estimate |
-| `nakagami_omega_per_frame/values` | `(20,z,x)` | `float32` | `a.u.^2` | Direct single-frame spread estimate |
-| `nakagami_m_pooled/values` | `(20,z,x)` | `float32` | `1` | 20-frame pooled shape reference |
-| `nakagami_omega_pooled/values` | `(20,z,x)` | `float32` | `a.u.^2` | 20-frame pooled spread reference |
+[zea v0.1.6](https://github.com/tue-bmd/zea)
 
-The five QUS products are zea Map fields with `values`, Cartesian `coordinates` in `[x,y,z]` order and metres, `description`, `unit`, `min`, and `max`. The BSC field also contains 157 `labels` of the form `frequency_hz=<value>`, spanning 3.3162435-6.4900716 MHz.
+Each file contains one track. Raw RF is stored as `int16` ADC counts without demodulation, decimation, or resampling. The five QUS targets are zea Map fields next to `raw_data`, with Cartesian coordinates in metres. The BSC field has 157 frequency `labels` (`frequency_hz=<value>`) spanning 3.3162435-6.4900716 MHz.
 
 Map grids are `(z,x)=(26,35)` for `15m` and `18m`, and `(53,35)` for `60m`. The analysis windows are approximately 2.96 mm axial by 4.37 mm lateral with 75% overlap. Nakagami maps use normal-incidence delay-and-sum beamforming, Hann receive apodization, and intensity-domain maximum-likelihood fitting, with `omega = E[A^2]`.
 
 The theoretical BSC is a homogeneous phantom material property: each phantom has one curve, broadcast over space and all 20 frames. The pooled Nakagami maps are also repeated along the frame axis so every single-frame input has the same 20-frame reference. The pooled estimate includes the selected input frame.
 
-Metadata uses `metadata.subject.type="phantom"` and a phantom ID. Anatomical annotations and anatomical-view annotations are intentionally omitted. Plane-wave acquisition is recorded in the file description, and the linear array geometry is recorded in the probe fields.
-
 ## Dataset Quantification
 
 **Current OpenH-RF release:** 120 HDF5 files; 1.00 GB (1,002,700,800 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.
 
-## Files
+- **Acquisitions / frames:** 120 acquisitions (3 phantoms x 2 operators x 20 probe placements, one HDF5 file each), 20 frames per acquisition — 2,400 frames total
+- **File naming:** `data/ac<n>_<phantom>_<operator>.hdf5`, with `n` from 1 to 20, e.g. `ac10_15m_SK.hdf5`
+- **Splits:** no predefined train/validation/test split. Keep all frames from one acquisition in the same split.
 
-```text
-data/<scan_id>.hdf5                         self-contained zea acquisitions
-reconstruct.py                              B-mode and QUS example
-pipeline.yaml                               zea reconstruction pipeline
-LICENSE                                     CC BY 4.0 license
-ac1_15m_SK_pipeline.png                     reference zea reconstruction
-```
+| Field under `tracks/track_0/data/` | Shape | dtype | Unit | Meaning |
+|---|---|---|---|---|
+| `raw_data` | `(20,1,n_ax,192,1)` | `int16` | ADC counts | Raw RF input |
+| `theoretical_bsc/values` | `(20,z,x,157)` | `float32` | `m^-1 sr^-1` | Model-derived BSC target |
+| `nakagami_m_per_frame/values` | `(20,z,x)` | `float32` | `1` | Direct single-frame shape estimate |
+| `nakagami_omega_per_frame/values` | `(20,z,x)` | `float32` | `a.u.^2` | Direct single-frame spread estimate |
+| `nakagami_m_pooled/values` | `(20,z,x)` | `float32` | `1` | 20-frame pooled shape reference |
+| `nakagami_omega_pooled/values` | `(20,z,x)` | `float32` | `a.u.^2` | 20-frame pooled spread reference |
 
-Scan IDs use `ac<number>_<phantom>_<operator>`, for example `ac1_15m_SK`. Phantom IDs are `15m`, `18m`, and `60m`; operator IDs are `SK` and `TP`; acquisition numbers run from 1 to 20.
+## Subject Metadata
 
-## Data Validation
+No human or animal subjects. `metadata/subject/type` is `phantom` and `metadata/subject/id` names the phantom (`phantom_15m`, `phantom_18m`, `phantom_60m`).
 
-The original 120 HDF5 files passed zea 0.1.3 `File.validate()` and `File.validate_spec()`. Raw RF and embedded maps were checked for shape, dtype, finite values, coordinates, labels, min/max, and the documented frame-broadcast behavior. The original files used zea 0.1.3's default Blosc/Zstd+bitshuffle compression.
+## Data Validation
 
-The reconstruction of `ac1_15m_SK` frame 0 is shown at the top of this card.
+A `zea.Pipeline` (cast → demodulate → DAS beamforming → envelope detection → normalization → log compression) is defined in `pipeline.yaml`, on a common 597 x 300 grid for every acquisition. Its output for frame 0 of `ac10_15m_SK` is shown at the top of this card. Raw RF and the embedded maps were checked for shape, dtype, finite values, coordinates, labels, min/max, and the frame-broadcast behavior described above.
 
 ## Known Issues
 
@@ -125,7 +115,6 @@ The reconstruction of `ac1_15m_SK` frame 0 is shown at the top of this card.
 - BSC targets are model-derived references, not independent experimental BSC measurements; there are three unique phantom curves.
 - Pooled Nakagami maps are lower-variance statistical references, not independent physical ground truth.
 - Nakagami `omega` depends on gain, attenuation, beam sensitivity, and RF amplitude scale; it is not system-independent.
-- This release contains Verasonics data only.
 
 ## Ethical Considerations