vanderbilt: restructure the data card to the common layout

vanderbilt/README.md

@@ -1,5 +1,6 @@
 ---
-pretty_name: "OpenH-RF — Vanderbilt / Multi-Frame Focused Transmit Echocardiography Channel Dataset"
+name: vanderbilt
+pretty_name: "Vanderbilt / Multi-Frame Focused Transmit Echocardiography Channel Dataset"
 license: cc-by-4.0
 task_categories:
   - image-reconstruction
@@ -17,33 +18,25 @@ size_categories:
   - n<1K
 ---
 
-# Multi-Frame Focused Transmit Echocardiography Channel Dataset
+# Vanderbilt Multi-Frame Focused Transmit Echocardiography Channel Dataset
 
 ![Cineloop of the left atrial appendage](assets/118420_1_Focused_Uncoded_TX.gif)
 
-One cineloop of a fundamental focused-transmit acquisition,
-[`data/Fundamental/118420_1_Focused_Uncoded_TX.hdf5`](https://huggingface.co/datasets/nvidia/OpenH-RF/blob/main/vanderbilt/data/Fundamental/118420_1_Focused_Uncoded_TX.hdf5).
-
-`zea` renders it straight from the Hub with the
-`pipeline.yaml` in this folder. Try it out with the following command:
-
-```bash
-zea process \
-  --dataset hf://nvidia/OpenH-RF/vanderbilt/data/Fundamental/118420_1_Focused_Uncoded_TX.hdf5 \
-  --config hf://nvidia/OpenH-RF/vanderbilt/pipeline.yaml \
-  --n-frames 10
-```
+*One cineloop of a fundamental focused-transmit acquisition, [`data/Fundamental/118420_1_Focused_Uncoded_TX.hdf5`](https://huggingface.co/datasets/nvidia/OpenH-RF/blob/main/vanderbilt/data/Fundamental/118420_1_Focused_Uncoded_TX.hdf5).*
 
 ## Dataset Description
 
 This multi-frame focused transmit echocardiography channel dataset contains over 2000 frames of fundamental and harmonic data acquired with the P4-2v probe on a Verasonics Vantage 128. This dataset was originally acquired to visualize the left atrial appendage in patients following transesophageal echocardiography. Some patients have atrial fibrillation, which can cause blood clots to form in the appendage.
 
-Each dataset follows the naming convention of `subject_id`_`view_number`_`sequence_type`. `subject_id` is a six-digit random number. `view_number` distinguishes between multiple views acquired on the same subject. `sequence_type` is either Focused_Uncoded_TX or Harmonic_Focused_Uncoded_TX. 
+Each dataset follows the naming convention of `subject_id`_`view_number`_`sequence_type`. `subject_id` is a six-digit random number. `view_number` distinguishes between multiple views acquired on the same subject. `sequence_type` is either Focused_Uncoded_TX or Harmonic_Focused_Uncoded_TX.
 
 ## Dataset Contributor(s)
 
-Brett Byram (PI), Christopher Khan, Ying-Chun (Preston) Pan, Zoe Marshall
-Vanderbilt University
+- Brett Byram (PI)
+- Christopher Khan
+- Ying-Chun (Preston) Pan
+- Zoe Marshall
+- Vanderbilt University
 
 ## Dataset Creation Date
 
@@ -51,7 +44,7 @@ Vanderbilt University
 
 ## License / Terms of Use
 
-CC BY 4.0.
+[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/legalcode.en). Retain attribution and identify modifications when reusing the data.
 
 ## Intended Usage
 
@@ -65,8 +58,27 @@ This dataset could be useful for training a domain-adaptive network, as it captu
 - **Frame rate:** Fundamental: 25 Hz (32 frames). Harmonic: 10 Hz (32 frames).
 - Note that the fundamental and harmonic sequences are not matched or interleaved: the harmonic sequence was executed immediately after the fundamental sequence within the same Verasonics setup file.
 
+## Processing the Dataset
+
+The acquisitions can be processed with the `pipeline.yaml` definition in this folder and the [zea library](https://github.com/tue-bmd/zea).
+
+`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:
+
+```bash
+zea process \
+  --dataset hf://nvidia/OpenH-RF/vanderbilt/data/Fundamental/118420_1_Focused_Uncoded_TX.hdf5 \
+  --config hf://nvidia/OpenH-RF/vanderbilt/pipeline.yaml \
+  --n-frames 10
+```
+
+Alternatively, you can use the `reconstruct.py` [script](https://github.com/open-h/OpenH-RF/blob/main/datasets/vanderbilt/reconstruct.py) as provided in the [OpenH-RF GitHub repository](https://github.com/open-h/OpenH-RF).
+
+Set `ZEA_FILE` and `N_FRAMES` at the top of the script to pick a file and how many frames to beamform.
+
 ## Dataset Format
 
+[zea v0.1.6](https://github.com/tue-bmd/zea)
+
 All acquisitions are submitted in the *zea* file format as raw RF channel data, with no preprocessing applied.
 
 | Group / field | Shape | Description |
@@ -75,27 +87,18 @@ All acquisitions are submitted in the *zea* file format as raw RF channel data,
 
 ### zea 0.1.6 Migration
 
-Files migrated with zea 0.1.6 store RF channel data at
-`tracks/track_0/data/raw_data`.
+Files migrated with zea 0.1.6 store RF channel data at `tracks/track_0/data/raw_data`.
 
-Two legacy scalar text fields are relocated because they are not standard
-zea 0.1.6 metadata fields:
+Two legacy scalar text fields are relocated because they are not standard zea 0.1.6 metadata fields:
 
 | Original path | Migrated path |
 |---|---|
 | `metadata/imaging_view_name` | `custom/legacy_metadata/imaging_view_name` |
 | `metadata/notes` | `custom/legacy_metadata/notes` |
 
-The scalar text values, string dtypes, and original attributes are preserved.
-Each relocated field also has a `source_hdf5_path` attribute recording its
-original path. No text is reinterpreted or cleaned by this relocation.
-The RF data are re-saved, without intentional filtering, normalization, or
-other numerical preprocessing. This schema migration is not an additional
-de-identification pass.
+The scalar text values, string dtypes, and original attributes are preserved. Each relocated field also has a `source_hdf5_path` attribute recording its original path. No text is reinterpreted or cleaned by this relocation. The RF data are re-saved, without intentional filtering, normalization, or other numerical preprocessing. This schema migration is not an additional de-identification pass.
 
-The current release uses the migrated schema; inspect each file's root
-`zea_version` attribute and field paths when loading it. The descriptions in
-Subject Metadata below apply to both the original and migrated text fields.
+The current release uses the migrated schema; inspect each file's root `zea_version` attribute and field paths when loading it. The descriptions in Subject Metadata below apply to both the original and migrated text fields.
 
 ## Dataset Quantification
 
@@ -103,8 +106,7 @@ Subject Metadata below apply to both the original and migrated text fields.
 
 - **Samples:** 82 cineloops (32 frames each) from 30 patients — 2,624 fundamental frames
 - Plus a matching set of 2,624 harmonic frames (same cineloops, harmonic sequence)
-- Plus one CIRS phantom validation acquisition (`CIRS_validation/CIRS_fundamental.hdf5`,
-  32 frames), giving the 165 files and 5,280 frames of the current release
+- Plus one CIRS phantom validation acquisition (`CIRS_validation/CIRS_fundamental.hdf5`, 32 frames), giving the 165 files and 5,280 frames of the current release
 - **Train / validation / test split:** N/A
 
 ## Subject Metadata
@@ -114,7 +116,7 @@ Subject Metadata below apply to both the original and migrated text fields.
 
 ## Data Validation
 
-A `zea.Pipeline` (cast → demodulate → DAS beamforming → envelope detection → normalization → log compression → scan conversion) reconstructs the B-mode image from the raw channel data and is defined in [pipeline.yaml](pipeline.yaml). Run [reconstruct.py](https://github.com/open-h/OpenH-RF/blob/main/datasets/vanderbilt/reconstruct.py) to reproduce it; set `INPUT` and `N_FRAMES` at the top of the script to pick a file and how many frames to beamform.
+A `zea.Pipeline` (cast → demodulate → DAS beamforming → envelope detection → normalization → log compression → scan conversion) reconstructs the B-mode image from the raw channel data and is defined in `pipeline.yaml`.
 
 ## Known Issues