dartmouth-uct: restructure the data card to the common layout

dartmouth-uct/README.md

@@ -1,44 +1,47 @@
-# OpenH-RF Sub-Dataset: 2D Ring-Array USCT Waveforms from 2D- and 3D-k-Wave Simulations
+---
+name: dartmouth-uct
+pretty_name: "2D Ring-Array USCT Waveforms from 2D- and 3D-k-Wave Simulations"
+license: cc-by-4.0
+task_categories:
+  - other
+tags:
+  - ultrasound
+  - rf
+  - openh-rf
+  - usct
+  - sound-speed-estimation
+  - attenuation
+  - breast
+  - simulation
+language:
+  - en
+size_categories:
+  - 1K<n<10K
+---
+
+# 2D Ring-Array USCT Waveforms from 2D- and 3D-k-Wave Simulations
 
 ![Ring-array USCT reflectivity reconstruction of a digital breast phantom, next to its ground-truth sound-speed and attenuation maps](assets/phantom_179604449_z200.png)
 
-A 2D-sim breast cross-section,
-[`data/2d/phantom_179604449_z200.hdf5`](https://huggingface.co/datasets/nvidia/OpenH-RF/blob/main/dartmouth-uct/data/2d/phantom_179604449_z200.hdf5),
-reconstructed by [`reconstruct.py`](https://github.com/open-h/OpenH-RF/blob/main/datasets/dartmouth-uct/reconstruct.py) beside the ground-truth sound-speed
-and attenuation maps stored in the file.
+*A 2D-sim breast cross-section, [`data/2d/phantom_179604449_z200.hdf5`](https://huggingface.co/datasets/nvidia/OpenH-RF/blob/main/dartmouth-uct/data/2d/phantom_179604449_z200.hdf5), reconstructed as a reflectivity image beside the ground-truth sound-speed and attenuation maps stored in the file.*
 
 ## Dataset Description
 
-This sub-dataset provides **pre-beamformed channel-domain radio-frequency
-ultrasound waveforms** from simulated ring-array **ultrasound computed
-tomography (USCT)** acquisitions of digital breast phantoms. All data are
-two-dimensional: each acquisition is a 2D channel tensor (transmit × time ×
-receiver) recorded at a 256-element ring as every element fires in turn, paired
-with 2D voxel-level ground-truth maps of **speed-of-sound (SOS)** and **acoustic
-attenuation** for a single breast cross-section.
-
-What distinguishes the two collections is **the k-Wave simulation used to
-generate the RF**:
-
-- **2D-sim** (2,149 acquisitions): RF computed with **2D** k-Wave
-  (`kspaceFirstOrder2D`) on the breast cross-section.
-- **3D-sim** (476 acquisitions): RF computed with **3D** k-Wave
-  (`kspaceFirstOrder3D`) on the full breast volume, then recorded at the ring
-  plane. The 3D simulation captures out-of-plane propagation and finite
-  focused-element behaviour that a 2D simulation cannot represent.
-
-Both collections are generated from the **same underlying digital breast
-phantoms** (derived from the open VICTRE breast model), enabling direct study of
-how 3D acoustic effects change the channel data relative to an idealized 2D
-simulation. All data are **synthetic (simulated)**; no human or animal subjects
-are involved.
+This sub-dataset provides **pre-beamformed channel-domain radio-frequency ultrasound waveforms** from simulated ring-array **ultrasound computed tomography (USCT)** acquisitions of digital breast phantoms. All data are two-dimensional: each acquisition is a 2D channel tensor (transmit × time × receiver) recorded at a 256-element ring as every element fires in turn, paired with 2D voxel-level ground-truth maps of **speed-of-sound (SOS)** and **acoustic attenuation** for a single breast cross-section.
+
+What distinguishes the two collections is **the k-Wave simulation used to generate the RF**:
+
+- **2D-sim** (2,149 acquisitions): RF computed with **2D** k-Wave (`kspaceFirstOrder2D`) on the breast cross-section.
+- **3D-sim** (476 acquisitions): RF computed with **3D** k-Wave (`kspaceFirstOrder3D`) on the full breast volume, then recorded at the ring plane. The 3D simulation captures out-of-plane propagation and finite focused-element behaviour that a 2D simulation cannot represent.
+
+Both collections are generated from the **same underlying digital breast phantoms** (derived from the open VICTRE breast model), enabling direct study of how 3D acoustic effects change the channel data relative to an idealized 2D simulation. All data are **synthetic (simulated)**; no human or animal subjects are involved.
 
 ## Dataset Contributor(s)
 
-- **Contributing organizations:** Thayer School of Engineering, Dartmouth
-  College; University of Rochester Medical Center.
-- **Primary point of contact:** Yujia Wu — `yujia.wu.th@dartmouth.edu`
-- **PI:** Prof. Geoffrey P. Luke — `Geoffrey.P.Luke@dartmouth.edu`
+- Yujia Wu <yujia.wu.th@dartmouth.edu> (primary point of contact)
+- Geoffrey P. Luke <Geoffrey.P.Luke@dartmouth.edu> (PI)
+- Thayer School of Engineering, Dartmouth College
+- University of Rochester Medical Center
 
 ## Dataset Creation Date
 
@@ -46,27 +49,20 @@ are involved.
 
 ## License / Terms of Use
 
-**CC BY 4.0.** All contributed data are cleared for this license. The data are
-fully synthetic (no patient data, no consent or IRB requirements). The digital
-breast phantoms derive from the publicly available VICTRE model (U.S. FDA / NCI,
-public domain).
+[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
 
 - **Sound-speed estimation / imaging** (quantitative SOS reconstruction).
 - **Acoustic-attenuation imaging.**
-- **Ultrasound computed tomography (USCT)** reconstruction from full-ring
-  channel data.
-- **Compressed sensing** — sub-sampling along the transmit
-  (Tx) or receive (Rx) axis and recovering missing channels.
+- **Ultrasound computed tomography (USCT)** reconstruction from full-ring channel data.
+- **Compressed sensing** — sub-sampling along the transmit (Tx) or receive (Rx) axis and recovering missing channels.
 
 ## Dataset Characterization
 
 - **Data Collection Method:** synthetic (k-Wave simulation).
-- **Labeling Method:** synthetic ground truth (voxel-level SOS and attenuation
-  maps are the exact simulation inputs; no annotation error).
-- **Acquisition system** (the label denotes the k-Wave simulation dimensionality;
-  the recorded data are 2D in both cases):
+- **Labeling Method:** synthetic ground truth (voxel-level SOS and attenuation maps are the exact simulation inputs; no annotation error).
+- **Acquisition system** (the label denotes the k-Wave simulation dimensionality; the recorded data are 2D in both cases):
 
 **2D-sim** (RF from 2D k-Wave)
 
@@ -98,47 +94,32 @@ public domain).
 | Time samples (T) | 2161 |
 | Record length | ~180 µs |
 
+## Processing the Dataset
+
+The acquisitions can be processed with the `reconstruct.py` [script](https://github.com/open-h/OpenH-RF/blob/main/datasets/dartmouth-uct/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.
+
+Set `ZEA_FILE` at the top of the script and run `python reconstruct.py`; the figure at the top of this card is its output. `SOS_MAP = True` swaps the constant-sound-speed delays for a straight-ray integral through the ground-truth map.
+
 ## Dataset Format
 
-All data are packaged in the **`zea` HDF5 file format** (one `.hdf5` file per
-acquisition), written entirely through `zea.File.create`. Each file stores the
-raw channel data under `tracks/track_0/data/raw_data`, the acquisition parameters
-under `tracks/track_0/scan`, the ring geometry under `probe` (in the **XZ imaging
-plane**, y = elevation), and the voxel-level ground truth as native zea map fields
-`tracks/track_0/data/sos_map` and `tracks/track_0/data/attenuation_map` (each with
-per-pixel `coordinates`). Tissue class is stored in `metadata/annotations`
-(`anatomy`, `label`); only fields with no standard spec home (z-plane indices,
-element focus) are zea `CustomElement`s under the top-level `custom/` group. Files
-are laid out by simulation type: `data/2d/` (2D-sim) and `data/3d/` (3D-sim).
+[zea v0.1.6](https://github.com/tue-bmd/zea)
+
+All data are packaged in the **`zea` HDF5 file format** (one `.hdf5` file per acquisition), written entirely through `zea.File.create`. Each file stores the raw channel data under `tracks/track_0/data/raw_data`, the acquisition parameters under `tracks/track_0/scan`, the ring geometry under `probe` (in the **XZ imaging plane**, y = elevation), and the voxel-level ground truth as native zea map fields `tracks/track_0/data/sos_map` and `tracks/track_0/data/attenuation_map` (each with per-pixel `coordinates`). Tissue class is stored in `metadata/annotations` (`anatomy`, `label`); only fields with no standard spec home (z-plane indices, element focus) are zea `CustomElement`s under the top-level `custom/` group. Files are laid out by simulation type: `data/2d/` (2D-sim) and `data/3d/` (3D-sim).
 
 **Pre-processing applied before packaging:**
-- 2D-sim: temporal decimation by 3× (20 MHz → 6.67 MHz native simulation rate).
-  3D-sim: saved at the native 12 MHz, no decimation.
-- Time-zero is carried in `scan/initial_times`; the per-sample time vector is
-  `initial_times[tx] + n / sampling_frequency`. In **both** sets `t = 0` is the
-  emission centroid: `initial_times = -2.15e-6` (2D-sim) and `-1.625e-6` (3D-sim,
-  the 5-cycle toneburst centroid). The 3D simulation saved its time vector from
-  the pulse onset, so this centroid offset is applied during conversion.
-- Single-element transmit events are described by `scan/tx_apodizations` with zero
-  `scan/t0_delays`. **2D-sim:** all 256 elements fire (identity matrix).
-  **3D-sim:** 64 events fire every 4th element (a `(64, 256)` stride-4 matrix).
-- Per-acquisition channel data stored as `float32` (zea's `raw_data` spec allows
-  only `float32` or `int16`). The 2D-sim RF was decimated and intermediately
-  cached at fp16 precision, so its stored `float32` is bit-faithful to that source
-  rather than carrying extra precision; the 3D-sim RF is the native `float32`
-  simulation output.
+- 2D-sim: temporal decimation by 3× (20 MHz → 6.67 MHz native simulation rate). 3D-sim: saved at the native 12 MHz, no decimation.
+- Time-zero is carried in `scan/initial_times`; the per-sample time vector is `initial_times[tx] + n / sampling_frequency`. In **both** sets `t = 0` is the emission centroid: `initial_times = -2.15e-6` (2D-sim) and `-1.625e-6` (3D-sim, the 5-cycle toneburst centroid). The 3D simulation saved its time vector from the pulse onset, so this centroid offset is applied during conversion.
+- Single-element transmit events are described by `scan/tx_apodizations` with zero `scan/t0_delays`. **2D-sim:** all 256 elements fire (identity matrix). **3D-sim:** 64 events fire every 4th element (a `(64, 256)` stride-4 matrix).
+- Per-acquisition channel data stored as `float32` (zea's `raw_data` spec allows only `float32` or `int16`). The 2D-sim RF was decimated and intermediately cached at fp16 precision, so its stored `float32` is bit-faithful to that source rather than carrying extra precision; the 3D-sim RF is the native `float32` simulation output.
 - No demodulation or beamforming is applied — data are raw RF channel signals.
 
 ## Dataset Quantification
 
 **Current OpenH-RF release:** 2,625 HDF5 files; 257.62 GB (257,619,787,776 bytes) stored; root `zea_version` **0.1.6**. Sizes include all HDF5 contents and use decimal units (MB = 10^6 bytes, GB = 10^9 bytes, TB = 10^12 bytes), not decoded-array memory or original-source download sizes.
 
-- **Number of acquisitions:** **2,149 (2D-sim)** (1,859 dense + 290 fatty) +
-  **476 (3D-sim)** = **2,625 acquisitions**.
-- **Single-Tx channel-capture frames:** 2,149 × 256 (2D-sim) + 476 × 64 (3D-sim)
-  ≈ **5.8 × 10⁵ frames**.
-- **Train / val / test split:** suggested 80 / 10 / 10 by **source phantom**
-  (so slices/z-planes from one phantom never cross splits — prevents leakage).
+- **Number of acquisitions:** **2,149 (2D-sim)** (1,859 dense + 290 fatty) + **476 (3D-sim)** = **2,625 acquisitions**.
+- **Single-Tx channel-capture frames:** 2,149 × 256 (2D-sim) + 476 × 64 (3D-sim) ≈ **5.8 × 10⁵ frames**.
+- **Train / val / test split:** suggested 80 / 10 / 10 by **source phantom** (so slices/z-planes from one phantom never cross splits — prevents leakage).
 - **Stored HDF5 size:** 257.62 GB total; 198.10 GB (2D-sim) + 59.52 GB (3D-sim).
 
 **Per-sample feature table — 2D-sim** (HDF5 keys per `.hdf5` acquisition):
@@ -161,9 +142,7 @@ are laid out by simulation type: `data/2d/` (2D-sim) and `data/3d/` (3D-sim).
 | `metadata/annotations` | – | str | – | `anatomy="breast"`, `label="dense"`/`"fatty"` |
 | `custom/z_slice` | scalar | int | – | Phantom z-slice index |
 
-Attenuation is stored in the zea base unit **dB/m/Hz** (`1 dB/cm/MHz = 1e-4
-dB/m/Hz`); the `sos_map`/`attenuation_map` `coordinates` carry the physical grid
-(so `dx` is implicit), and `scan/sound_speed` holds the water reference.
+Attenuation is stored in the zea base unit **dB/m/Hz** (`1 dB/cm/MHz = 1e-4 dB/m/Hz`); the `sos_map`/`attenuation_map` `coordinates` carry the physical grid (so `dx` is implicit), and `scan/sound_speed` holds the water reference.
 
 **Per-sample feature table — 3D-sim** (HDF5 keys per `.hdf5` acquisition):
 
@@ -186,66 +165,32 @@ dB/m/Hz`); the `sos_map`/`attenuation_map` `coordinates` carry the physical grid
 | `metadata/annotations` | – | str | – | `anatomy="breast"` (no dense/fatty label for the 3D set) |
 | `custom/z_off`, `custom/phantom_z_idx`, `custom/element_focus` | scalar | int / float | – / m | Ring z-offset, phantom z-slice index, element focus (0.075 m) |
 
-Attenuation is in the zea base unit **dB/m/Hz**; the map `coordinates` carry the
-physical grid (XZ plane, y = 0).
+Attenuation is in the zea base unit **dB/m/Hz**; the map `coordinates` carry the physical grid (XZ plane, y = 0).
 
 ## Subject Metadata
 
 Not applicable — all data are synthetic. Aggregate phantom statistics:
 
-- **Anatomical region:** breast cross-sections. The 3D-sim set samples several
-  z-planes per phantom (one 2D cross-section each).
-- **Tissue classes represented:** fat, glandular, skin/connective, with
-  continuous SOS/attenuation/density assignments.
+- **Anatomical region:** breast cross-sections. The 3D-sim set samples several z-planes per phantom (one 2D cross-section each).
+- **Tissue classes represented:** fat, glandular, skin/connective, with continuous SOS/attenuation/density assignments.
 - **No PHI.**
 
 ## Data Validation
 
-A single reference reconstruction, [`reconstruct.py`](https://github.com/open-h/OpenH-RF/blob/main/datasets/dartmouth-uct/reconstruct.py), serves
-**both** sub-datasets. It builds a `zea.Pipeline` whose beamforming stage is
-zea's dedicated `zea.ops.USCTReflectivityDAS` — a round-trip time-of-flight
-Delay-And-Sum that, for every pixel, coherently sums over all transmit/receive
-pairs, rejects the direct through-transmission arrival, and apodizes to keep only
-backscatter geometries. The pipeline is saved to [`pipeline.yaml`](pipeline.yaml).
-
-The same code reconstructs the 2D-sim (256 transmits) and 3D-sim (64 transmits)
-files because everything it needs is read **back from the zea file**: element
-positions (`probe/probe_geometry`), the transmit selection (`scan/tx_apodizations`),
-sampling rate (`scan/sampling_frequency`), time-zero (`scan/initial_times`), and
-the imaging grid (from the ground-truth `coordinates`). The ring is stored in the
-XZ imaging plane, so `zea.File.load_parameters` + `pipeline.prepare_parameters`
-drive the reconstruction directly. A resulting image whose bright skin boundary
-traces the ground-truth contour confirms the geometry, timing, and transmit
-parameters were recorded correctly.
-
-Set `ZEA_FILE` at the top of the script and run `python reconstruct.py`; the
-figure at the top of this card is its output. `SOS_MAP = True` swaps the
-constant-sound-speed delays for a straight-ray integral through the
-ground-truth map.
+A single reference reconstruction, `reconstruct.py` (see *Processing the Dataset*), serves **both** sub-datasets. It builds a `zea.Pipeline` whose beamforming stage is zea's dedicated `zea.ops.USCTReflectivityDAS` — a round-trip time-of-flight Delay-And-Sum that, for every pixel, coherently sums over all transmit/receive pairs, rejects the direct through-transmission arrival, and apodizes to keep only backscatter geometries. The pipeline is saved to [`pipeline.yaml`](pipeline.yaml).
+
+The same code reconstructs the 2D-sim (256 transmits) and 3D-sim (64 transmits) files because everything it needs is read **back from the zea file**: element positions (`probe/probe_geometry`), the transmit selection (`scan/tx_apodizations`), sampling rate (`scan/sampling_frequency`), time-zero (`scan/initial_times`), and the imaging grid (from the ground-truth `coordinates`). The ring is stored in the XZ imaging plane, so `zea.File.load_parameters` + `pipeline.prepare_parameters` drive the reconstruction directly. A resulting image whose bright skin boundary traces the ground-truth contour confirms the geometry, timing, and transmit parameters were recorded correctly.
 
 ## Known Issues
 
-- **2D-sim vs 3D-sim differ in geometry and sampling** — 60 mm vs 110.9 mm ring;
-  256 vs 64 transmits; 867 @ 6.67 MHz (130 µs) vs 2161 @ 12 MHz (~180 µs); 230²
-  (0.30 mm) vs 800² (0.29 mm) GT maps. Users combining both must resample to a
-  common grid.
-- **2D-sim point elements vs 3D-sim focused elements:** the 2D-sim set idealizes
-  elements as points (no element directivity), while the 3D-sim set models finite
-  focused elements (0.558 mm × 19 mm, 75 mm elevation focus) and out-of-plane
-  propagation.
-- **Attenuation units:** stored in the zea base unit `dB/m/Hz` (converted from the
-  simulation's `dB/cm/MHz`; `1 dB/cm/MHz = 1e-4 dB/m/Hz`). The k-Wave `alpha_power`
-  is the `attenuation_map/gamma` field (α(f)=α₀·fᵞ, γ=1.01).
-- **Time-zero convention:** in both sets `t = 0` is the emission centroid (carried
-  in `scan/initial_times`), not the first recorded sample — important for
-  time-of-flight methods.
+- **2D-sim vs 3D-sim differ in geometry and sampling** — 60 mm vs 110.9 mm ring; 256 vs 64 transmits; 867 @ 6.67 MHz (130 µs) vs 2161 @ 12 MHz (~180 µs); 230² (0.30 mm) vs 800² (0.29 mm) GT maps. Users combining both must resample to a common grid.
+- **2D-sim point elements vs 3D-sim focused elements:** the 2D-sim set idealizes elements as points (no element directivity), while the 3D-sim set models finite focused elements (0.558 mm × 19 mm, 75 mm elevation focus) and out-of-plane propagation.
+- **Attenuation units:** stored in the zea base unit `dB/m/Hz` (converted from the simulation's `dB/cm/MHz`; `1 dB/cm/MHz = 1e-4 dB/m/Hz`). The k-Wave `alpha_power` is the `attenuation_map/gamma` field (α(f)=α₀·fᵞ, γ=1.01).
+- **Time-zero convention:** in both sets `t = 0` is the emission centroid (carried in `scan/initial_times`), not the first recorded sample — important for time-of-flight methods.
 
 ## Ethical Considerations
 
-Fully synthetic dataset. No human or animal subjects; no consent, IRB, or
-de-identification requirements apply. The VICTRE breast phantoms are publicly
-released by the U.S. FDA/NCI. No usage caveats beyond the CC BY 4.0 attribution
-requirement.
+Fully synthetic dataset. No human or animal subjects; no consent, IRB, or de-identification requirements apply. The VICTRE breast phantoms are publicly released by the U.S. FDA/NCI. No usage caveats beyond the CC BY 4.0 attribution requirement.
 
 ---
 
@@ -253,9 +198,5 @@ requirement.
 
 If you use this sub-dataset, please cite:
 
-- Badano A, Graff CG, Badal A, Sharma D, Zeng R, Samuelson FW, Glick SJ,
-  Myers KJ. *Evaluation of Digital Breast Tomosynthesis as Replacement of
-  Full-Field Digital Mammography Using an In Silico Imaging Trial.*
-  JAMA Network Open. 2018;1(7):e185474. doi:10.1001/jamanetworkopen.2018.5474
-- Treeby BE, Cox BT. *k-Wave: MATLAB toolbox for the simulation and
-  reconstruction of photoacoustic wave fields.* J Biomed Opt. 2010;15(2):021314.
+- Badano A, Graff CG, Badal A, Sharma D, Zeng R, Samuelson FW, Glick SJ, Myers KJ. *Evaluation of Digital Breast Tomosynthesis as Replacement of Full-Field Digital Mammography Using an In Silico Imaging Trial.* JAMA Network Open. 2018;1(7):e185474. doi:10.1001/jamanetworkopen.2018.5474
+- Treeby BE, Cox BT. *k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields.* J Biomed Opt. 2010;15(2):021314.