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+nv-raw2insights-us/data/nv_r2i_us_validation_0088.hdf5 filter=lfs diff=lfs merge=lfs -text
+nv-raw2insights-us/data/nv_r2i_us_validation_0089.hdf5 filter=lfs diff=lfs merge=lfs -text
+nv-raw2insights-us/data/nv_r2i_us_validation_0090.hdf5 filter=lfs diff=lfs merge=lfs -text
+nv-raw2insights-us/data/nv_r2i_us_validation_0091.hdf5 filter=lfs diff=lfs merge=lfs -text
+nv-raw2insights-us/data/nv_r2i_us_validation_0092.hdf5 filter=lfs diff=lfs merge=lfs -text
diff --git a/nv-raw2insights-us/README.md b/nv-raw2insights-us/README.md
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+---
+pretty_name: "OpenH-RF — NV-Raw2Insights-US (simulated FSA, sound-speed / aberration / segmentation)"
+license: cc-by-4.0
+task_categories:
+  - other
+tags:
+  - ultrasound
+  - rf
+  - iq
+  - openh-rf
+  - beamforming
+  - sound-speed-estimation
+  - phase-aberration
+  - segmentation
+  - simulation
+language:
+  - en
+size_categories:
+  - n<1K
+---
+
+# NV-Raw2Insights-US — Simulated FSA Channel Data with Sound-Speed, Aberration, and Segmentation Ground Truth
+
+## Dataset Description
+
+NV-Raw2Insights-US is a **simulated full-synthetic-aperture (FSA)** ultrasound
+dataset for training and evaluating neural networks on **sound-speed
+estimation**, **phase-aberration correction**, **tissue segmentation**, and
+**learned image reconstruction** from raw pre-beamformed channel data.
+
+Each sample is a single-frame FSA acquisition from a **180-element linear
+array** simulated with **k-Wave** over a heterogeneous tissue phantom
+containing cysts. Every acquisition provides raw baseband **IQ channel data**
+alongside co-registered ground truth: a **speed-of-sound map**, a **binary cyst
+segmentation mask**, a **DAS B-mode** and a **focused-transmit B-mode**, and a
+per-sample **phase-aberration** value. All data are **synthetic**; no human or
+animal subjects are involved.
+
+This is the **zea-format (OpenH-RF) release**; the same simulations are also
+published in a Hugging Face `datasets`/Arrow build at
+[`nvidia/NV-Raw2Insights-US`](https://huggingface.co/datasets/nvidia/NV-Raw2Insights-US).
+
+## Dataset Contributor(s)
+
+NVIDIA Corporation — Walter Simson, Sean Huver.
+
+## Dataset Creation Date
+
+12/01/2025.
+
+## 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.
+
+## Intended Usage
+
+Developing and benchmarking methods that operate on raw ultrasound channel data:
+learned/adaptive beamforming, sound-speed estimation, phase-aberration
+correction, and tissue segmentation. Because the sound-speed map, segmentation
+mask, and aberration value are exact simulation ground truth, the dataset
+supports fully-supervised training of channel-data-to-insight models.
+
+## Dataset Characterization
+
+- **Data Collection Method:** Synthetic — k-Wave acoustic simulation of a
+  180-element linear array over heterogeneous tissue phantoms with cysts.
+- **Labeling Method:** Synthetic — ground truth taken directly from the
+  simulation parameters (sound-speed map, cyst segmentation, aberration).
+- **Acquisition model:** Full synthetic aperture (multi-static) — 180
+  single-element transmit events per frame, all 180 elements received;
+  transmit centre frequency 6.5 MHz, baseband IQ sampled at 13.3 MHz,
+  background sound speed 1540 m/s.
+
+## Dataset Format
+
+Packaged in the **zea** file format (`zea_version` 0.1.0), **one HDF5 file per
+sample**, all under `data/`. The train/validation split is encoded in each
+filename (`nv_r2i_us_train_XXXX.hdf5`, `nv_r2i_us_validation_XXXX.hdf5`).
+
+Per-file contents:
+
+| Group / field | Shape | Dtype | Units | Description |
+| --- | --- | --- | --- | --- |
+| `tracks/track_0/data/raw_data` | `[1, 180, 1024, 180, 2]` | float32 | – | Baseband IQ channel data `[frame, transmit, fast-time, receive, (I,Q)]` |
+| `tracks/track_0/data/image` (+ `coordinates`) | `[1, 507, 456]` | uint8 | – | Synthetic-aperture DAS B-mode reconstructed from `raw_data` |
+| `tracks/track_0/data/bmode_focused` (+ `coordinates`) | `[1, 507, 456]` | uint8 | – | Focused-transmit B-mode |
+| `tracks/track_0/data/sos_map` (+ `coordinates`, `unit`) | `[1, 32, 32]` | float32 | m/s | Ground-truth speed-of-sound map |
+| `tracks/track_0/data/segmentation` (+ `coordinates`, `labels`) | `[1, 507, 456, 2]` | bool | – | Binary segmentation; `labels` name the classes (background tissue / cyst) |
+| `metrics/common_midpoint_phase_error` | `[1]` | float32 | rad | Per-sample phase-aberration error |
+| `tracks/track_0/scan/{sampling,center,demodulation}_frequency` | scalar | float32 | Hz | 13.3 MHz / 6.5 MHz / 6.5 MHz |
+| `tracks/track_0/scan/sound_speed` | scalar | float32 | m/s | Background sound speed (1540) |
+| `tracks/track_0/scan/{initial_times, t0_delays, tx_apodizations, transmit_origins, focus_distances, polar_angles, azimuth_angles}` | per-transmit | float32 | s / – / m / rad | Full-synthetic-aperture transmit description (single-element transmits) |
+| `probe/probe_geometry` | `[180, 3]` | float32 | m | Element positions (x, y, z) |
+| `probe/name` | str | – | – | Transducer identifier |
+| `metadata/annotations/{anatomy, label}`, `metadata/subject/type`, `metadata/credit` | str | – | – | Aggregate/de-identified metadata (subject type = simulation) |
+
+## Dataset Quantification
+
+- **923 samples (830 train / 93 validation)**, one HDF5 per sample, all in
+  `data/`; the split is carried in the filename.
+- Each sample is a single-frame FSA acquisition (frame index always 0).
+
+## Subject Metadata
+
+- **Synthetic only** — no human or animal subjects. Each sample is a k-Wave
+  simulation over a digital tissue phantom containing cysts.
+- No PHI; `subject/type` is a simulation label, not a patient identifier.
+
+## Data Validation
+
+Each file's `tracks/track_0/data/image` is a DAS B-mode reconstructed from
+`raw_data` by the zea pipeline (see `pipeline.yaml`), so the reconstruction is
+reproducible from the raw channel data and the recorded transmit description.
+
+## Known Issues
+
+- `sos_map` is a coarse `32 × 32` grid while the B-mode and segmentation are on
+  the fine `507 × 456` grid; each carries its own `coordinates` for alignment.
+- Cysts that touch the edge of the B-mode frame are not included in the
+  segmentation mask.
+- Some regions of gross reverberation artifact can be incorrectly segmented as
+  cysts.
+
+## Ethical Considerations
+
+The data are entirely synthetic (k-Wave simulation of digital phantoms). There
+are no human participants, animal subjects, patient identifiers, or protected
+health information. Released under CC BY 4.0 for research and technical
+evaluation, not clinical decision-making.
+
+## Citation
+
+```bibtex
+@misc{nv_raw2insights_us_2026,
+  title={NV-Raw2Insights-US},
+  author={Simson, Walter and Huver, Sean},
+  year={2026},
+  publisher={NVIDIA Corporation},
+  howpublished={\url{https://huggingface.co/datasets/nvidia/NV-Raw2Insights-US}},
+  license={CC BY 4.0}
+}
+```
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