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README.md

@@ -1,38 +1,112 @@
 ---
-license: other
+license: cc-by-nc-sa-4.0
 zea_repo_id: zeahub/echoxflow
-task_categories:
-  - image-classification
+pretty_name: "EchoXFlow 2-D B-mode subset (zea format)"
 tags:
   - ultrasound
   - echocardiography
-  - 2d
   - cardiac
-  - medical
-pretty_name: "EchoXFlow 2-D B-mode (zea format)"
+  - medical-imaging
+  - beamspace
+  - ecg
+  - zea
+size_categories:
+  - 10K<n<100K
+source_datasets:
+  - Ahus-AIM/EchoXFlow
 ---
 
-# EchoXFlow - 2-D B-mode Ultrasound Dataset
+# EchoXFlow - 2-D B-mode subset (zea format)
 
-This dataset is a **zea-format** (HDF5) conversion of the EchoXFlow
-``2d_brightness_mode`` recordings, hosted at
-[zeahub/echoxflow](https://huggingface.co/datasets/zeahub/echoxflow).
+> **This is a derived, partial copy of [EchoXFlow](https://huggingface.co/datasets/Ahus-AIM/EchoXFlow)
+> by Stenhede et al. (Akershus University Hospital).** All credit for the data goes to the original
+> authors. Please cite their [paper](https://arxiv.org/abs/2605.05447) (see [Citation](#citation)) and
+> use the [original dataset](https://huggingface.co/datasets/Ahus-AIM/EchoXFlow) if you need the full data.
 
-## Conversion
+- **Paper:** [EchoXFlow: A Beamspace Echocardiography Dataset for Cardiac Motion, Flow, and Function](https://arxiv.org/abs/2605.05447) (NeurIPS 2026 Datasets and Benchmarks)
+- **Original dataset:** [Ahus-AIM/EchoXFlow](https://huggingface.co/datasets/Ahus-AIM/EchoXFlow)
+- **Code:** [github.com/Ahus-AIM/EchoXFlow](https://github.com/Ahus-AIM/EchoXFlow)
+- **License:** [CC BY-NC-SA 4.0](LICENSE), inherited from the original dataset
 
-This dataset was converted to zea format and uploaded using the
-[zea](https://github.com/tue-bmd/zea) data converter:
+EchoXFlow contains 666 routine-care echocardiographic examinations (35,377 recordings) stored in the
+scanner's native beamspace (polar) grid, with co-registered ECG, B-mode, Doppler and dense/sparse
+annotations. This repository re-packages **only the single-plane 2-D B-mode recordings** into the
+[zea](https://github.com/tue-bmd/zea) HDF5 format, so they can be loaded directly with zea.
+
+## What is included
+
+| | |
+|---|---|
+| **Recordings** | 13,619 single-plane 2-D B-mode recordings (of 26,356 in EchoXFlow) |
+| **Examinations** | 666 (all) |
+| **Selection** | frame rate > 30 Hz and >= 10 frames |
+| **Per file** | B-mode frames (`uint8`, beamspace / polar grid, not scan-converted), per-pixel Cartesian coordinates, frame timestamps, ECG (when available), exam id |
+| **Size** | ~276 GB |
 
-```bash
-python -m zea.data.convert echoxflow <src> <dst>
 ```
+data/
+  <exam_id>/
+    <recording_id>.hdf5
+```
+
+The exam id is stored as `metadata/subject/id`, but it identifies an **examination, not a patient**: one
+patient can have several exams. Do not use it for patient-disjoint splits; use `splits.csv` from the
+original dataset instead.
+
+## Limitations and differences from the original
+
+This is **not** the full EchoXFlow dataset. Compared to the original it is missing:
+
+- All other modalities: M-mode, dual-plane, triplane and 3-D B-mode, colour/tissue Doppler, pulsed- and continuous-wave Doppler.
+- Single-plane B-mode recordings with frame rate <= 30 Hz or fewer than 10 frames (e.g. probe-positioning or single-frame captures).
+- All annotations (speckle-tracking contours, 3-D LV meshes, sample volumes, measurements, spectral traces, QRS triggers).
+- Most recording metadata from the Zarr stores and `croissant.json` (e.g. `derived/` quantities, acquisition parameters beyond sector geometry, SHA-256 checksums).
+- `splits.csv` (patient-level five-fold split) and `view_classifier_probabilities.csv` (view labels). Use the files from the
+  [original repository](https://huggingface.co/datasets/Ahus-AIM/EchoXFlow) with the `exam_id` / `recording_id` from the file paths.
+
+The conversion was made from the EchoXFlow release available in June 2026; later upstream changes are not reflected here.
+
+The limitations of the original dataset also apply: single-centre, single-vendor data from a selected population. It is not
+representative of all institutions, vendors, protocols or patient subgroups, and it is not validated for clinical diagnosis,
+triage, treatment or prognosis.
 
-## Dataset structure
+## Usage
 
+```python
+import zea
+
+path = "hf://zeahub/echoxflow/data/exam_0068f33be3ce3c27/recording_0110895d4a45b99e.hdf5"
+with zea.File(path) as f:
+    image = f.tracks[0].data.image
+    frames = image.values[:]       # (n_frames, n_depth, n_angles), uint8, beamspace
+    coords = image.coordinates[:]  # (n_depth, n_angles, 3), Cartesian (x, y, z) in metres
+    ecg = f.metadata.ecg.samples[:]
 ```
-<exam_id>/
-  <recording_id>.hdf5
-  ...
+
+The files were created with the zea converter (requires the [`echoxflow`](https://github.com/Ahus-AIM/EchoXFlow) package):
+
+```bash
+zea convert echoxflow <echoxflow_data_root> <dst> --min-frames 10 --min-fps 30
 ```
 
-Each HDF5 file follows the [zea data format](https://github.com/tue-bmd/zea).
+## License
+
+[CC BY-NC-SA 4.0](LICENSE), the same license as the original EchoXFlow dataset. You may share and adapt the data for
+**non-commercial** purposes, provided you give appropriate credit to the EchoXFlow authors, indicate changes, and
+distribute derivatives under the same license. Changes made here: the subset selection and format conversion described above.
+
+## Citation
+
+If you use this data, cite the original EchoXFlow paper:
+
+```bibtex
+@inproceedings{stenhede_2026_echoxflow,
+  title = {EchoXFlow: A Beamspace Echocardiography Dataset for Cardiac Motion, Flow, and Function},
+  author = {Stenhede, Elias and Sulkowska, Joanna and Orstad, Eivind Bj{\o}rkan and Schirmer, Henrik and Ranjbar, Arian},
+  booktitle = {Advances in Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track},
+  year = {2026},
+  eprint = {2605.05447},
+  doi = {10.48550/arXiv.2605.05447},
+  url = {https://arxiv.org/abs/2605.05447}
+}
+```