Add dataset card

README.md

@@ -1,108 +1,244 @@
 ---
-dataset_info:
-- config_name: annotated
-  features:
-  - name: image
-    dtype: image
-  - name: mask
-    dtype: image
-  - name: video_id
-    dtype: string
-  - name: folder
-    dtype: string
-  - name: site
-    dtype: string
-  - name: subject
-    dtype: string
-  - name: view
-    dtype: string
-  - name: split
-    dtype: string
-  - name: frame_index
-    dtype: int32
-  - name: n_frames
-    dtype: int32
-  - name: height
-    dtype: int32
-  - name: width
-    dtype: int32
-  - name: has_mask
-    dtype: bool
-  - name: gt_dense
-    dtype: bool
-  - name: gt_source
-    dtype: string
-  - name: mask_filled_from_contour
-    dtype: bool
-  - name: label_remapped
-    dtype: bool
-  - name: video_truncated
-    dtype: bool
-  - name: group_id
-    dtype: string
-  - name: deid_blanked_rows
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 179037353
-    num_examples: 2257
-  download_size: 178848651
-  dataset_size: 179037353
-- config_name: full_video
-  features:
-  - name: image
-    dtype: image
-  - name: mask
-    dtype: image
-  - name: video_id
-    dtype: string
-  - name: folder
-    dtype: string
-  - name: site
-    dtype: string
-  - name: subject
-    dtype: string
-  - name: view
-    dtype: string
-  - name: split
-    dtype: string
-  - name: frame_index
-    dtype: int32
-  - name: n_frames
-    dtype: int32
-  - name: height
-    dtype: int32
-  - name: width
-    dtype: int32
-  - name: has_mask
-    dtype: bool
-  - name: gt_dense
-    dtype: bool
-  - name: gt_source
-    dtype: string
-  - name: mask_filled_from_contour
-    dtype: bool
-  - name: label_remapped
-    dtype: bool
-  - name: video_truncated
-    dtype: bool
-  - name: group_id
-    dtype: string
-  - name: deid_blanked_rows
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 3130572528
-    num_examples: 38619
-  download_size: 3126242510
-  dataset_size: 3130572528
+license: apache-2.0
+pretty_name: CardiacUDC
+task_categories:
+  - image-segmentation
+tags:
+  - medical-imaging
+  - echocardiography
+  - ultrasound
+  - cardiac
+  - four-chamber
+  - 2d-echo
+  - video-segmentation
+size_categories:
+  - 10K<n<100K
 configs:
-- config_name: annotated
-  data_files:
-  - split: train
-    path: annotated/train-*
-- config_name: full_video
-  data_files:
-  - split: train
-    path: full_video/train-*
+  - config_name: annotated
+    default: true
+    data_files:
+      - split: train
+        path: annotated/train-*
+  - config_name: full_video
+    data_files:
+      - split: train
+        path: full_video/train-*
 ---
+
+# CardiacUDC — apical four-chamber echocardiography video segmentation
+
+2D transthoracic echocardiography from two hospitals ("Site G" and "Site R"),
+annotated for the four cardiac chambers. Introduced as **CardiacUDA** in
+[GraphEcho (ICCV 2023)](https://arxiv.org/abs/2309.11145); the Kaggle release
+spells it *cardiacUDC*. Converted from the official Kaggle release — see
+[Provenance](#provenance).
+
+This is a **video** dataset: 364 recordings, 38,619 frames, one row per frame.
+
+## Configs
+
+| Config | Rows | Contents | Mask |
+|---|---|---|---|
+| **`annotated`** *(default)* | **2,257** | every frame that carries ground truth | always present |
+| `full_video` | **38,619** | every frame of all 364 videos | present on 2,257, `null` elsewhere |
+
+`annotated` is exactly `full_video[has_mask == True]` — same schema, same rows.
+Use `annotated` for scoring; use `full_video` for temporal propagation, ordering
+by `frame_index` and grouping by `video_id`.
+
+## Classes
+
+| Value | Structure |
+|---|---|
+| 0 | background |
+| 1 | LV — left ventricle |
+| 2 | LA — left atrium |
+| 3 | RA — right atrium |
+| 4 | RV — right ventricle |
+
+**Value 2 is the left atrium, not the right ventricle; RV is 4.** The numbering
+walks the heart in a loop. This matches the authors' own loader
+([`datasets/cardiac_uda.py`](https://github.com/xmed-lab/GraphEcho/blob/main/datasets/cardiac_uda.py),
+view `'4'` branch). Figure 2 of the paper labels the left atrium "(RA)" and lists
+a fifth structure, "epicardium of left ventricle", which does not exist in this
+release.
+
+## Composition
+
+Seven source folders. No train/val/test directories ship.
+
+| Folder | Videos | With GT | Site |
+|---|---|---|---|
+| Site_G_100 | 97 | 97 | G |
+| Site_G_29 | 29 | 29 | G |
+| Site_G_20 | 21 | 21 | G |
+| Site_R_126 | 85 | 84 | R |
+| Site_R_52 | 52 | 52 | R |
+| Site_R_73 | 70 | **0** | R |
+| label_all_frame | 10 | 10 | mixed |
+| **Total** | **364** | **293** | |
+
+Folder-name numbers do not match their contents (`Site_G_100` holds 97,
+`Site_R_126` holds 85). Frame counts range 41–284 (mean 106). Three
+resolutions ship — 800×600 (335 videos), 1024×768 (24), 640×480 (5) — not the
+two the source description states.
+
+### Two annotation regimes
+
+- **`Site_*` folders — sparse.** 5–8 frames annotated per video (mean 5.9), out
+  of ~106. This is the paper's *training* annotation budget.
+- **`label_all_frame` — dense.** Every frame annotated, 548 frames over 10
+  videos. The paper's val/test analogue.
+
+`gt_dense` distinguishes them; `gt_source` records which pipeline produced each
+mask.
+
+## ⚠️ `label_all_frame` overlaps `Site_R_126` — do not split them apart
+
+Eight of the ten `label_all_frame` videos are **the same recordings** as videos
+in `Site_R_126`: same subject id, identical frame count, ~88% bit-identical
+pixels (mean absolute difference ≈4.5/255, correlation 0.70–0.94). They are a
+dense re-annotation of footage that also ships sparsely annotated, not new
+material. The remaining two have no `Site_*` counterpart.
+
+Putting `label_all_frame` in a test split and `Site_*` in train therefore leaks
+8 of 10 test videos into training. **`group_id` ties each twin pair together** —
+split on `group_id`, never on `video_id` or `subject`.
+
+## Splits
+
+**A single `train` split ships.** The paper's 8:1:1 division is not distributed,
+and the near-duplication above makes any naive split leak. Downstream consumers
+should construct their own split, grouping on `group_id`.
+
+## Subject ids are not unique
+
+85 subject names occur in more than one folder, and those collisions are
+**different recordings** (0 of 85 are byte-identical). `video_id` is
+`{folder}/{subject}` and is the only safe key. Grouping on bare `subject` will
+silently merge unrelated patients.
+
+## What this release changes from source
+
+Every modification below is deliberate and reversible from the original Kaggle
+archive; nothing else is altered.
+
+1. **Contour masks filled.** `label_all_frame` ships hollow ~1px contour
+   *outlines*, whereas `Site_*` ships filled regions. Scoring a raw outline
+   measures the rim, not the chamber. Outlines are filled per class with
+   `scipy.ndimage.binary_fill_holes` (with a 1–3 iteration `binary_closing`
+   fallback for open contours). Validated: post-fill area/bbox ratio is
+   **0.689**, against **0.68** for the natively-filled `Site_*` masks. Two class
+   instances out of ~2,150 could not be closed and were dropped rather than
+   shipped as rings. `mask_filled_from_contour` flags affected rows.
+
+   The authors' `contour_to_mask` was **not** used: it selects classes by rank
+   within `set(unique_values)`, so on a volume with a missing class it silently
+   renumbers the remaining ones.
+
+2. **Stray label values remapped.** Two `label_all_frame` volumes encode two of
+   the chambers as 5 and 6 instead of 1 and 4. Verified spatially against the
+   eight consistent volumes — the stray values sit at the class centroids of 1
+   and 4 (normalised distance 0.013–0.078, every value matching exactly one
+   class) — and remapped `{5→1, 6→4}`. `label_remapped` flags affected rows.
+
+3. **One truncated source file salvaged.** One `Site_R_126` label volume is a
+   truncated gzip **in the source archive** — the enclosing zip's CRC verifies,
+   so this is not a transfer defect. Its 42 intact frames (7 annotated) are
+   kept; the remaining 21 frames carry no ground truth. `video_truncated` flags
+   the video.
+
+4. **Orientation normalised.** Source arrays are `(W, H, T)`; each frame is
+   transposed and rotated 180° into the orientation in which the scanner's
+   on-screen text reads correctly. Applied identically to images and masks.
+
+5. **De-identification band.** The top `max(45, ceil(0.075 × H))` rows of every
+   frame of every video are zeroed — 45 rows at 480px and 600px, 58 at 768px.
+   Some source videos retained scanner header text containing patient
+   identifiers; the band is applied **uniformly to all 364 videos** rather than
+   selectively, so the redaction does not itself indicate which files were
+   affected. **This is a MedOtter modification — upstream is unmodified in this
+   respect.**
+
+   The band costs no annotation. Over all 294 label volumes / 2,257 annotated
+   frames at native resolution, the topmost mask row is 81 (480px), 83 (600px)
+   and 144 (768px), against a maximum blank of 58. The build re-checks this per
+   frame and refuses to write a row whose mask intersects the band.
+   `deid_blanked_rows` records the band height applied to each row.
+
+## Known limitations of the source release
+
+- **Only the A4C view ships.** The paper describes 992 videos across four views
+  (LVLA, PALA, LVSA, A4C); the public release is view 4 only, 364 videos. The
+  other three views and the pulmonary-artery class were announced for late 2024
+  and have not appeared — Kaggle remains at version 1 (2023-10-30).
+- **70 videos in `Site_R_73` have no labels at all**, and one `Site_R_126` label
+  volume is present but entirely empty. Both are shipped in `full_video` as
+  image-only rows and excluded from `annotated`.
+- Third-party catalogues describing this dataset as "5 structures (LV, RV, MYO,
+  LA, RA)" or "29,283 slices" do not match the public release.
+
+## Schema
+
+| Column | Type | Notes |
+|---|---|---|
+| `image` | Image | PNG, grayscale, de-identification band applied |
+| `mask` | Image | PNG, values 0–4; `null` where no GT |
+| `video_id` | string | `{folder}/{subject}` — the only unique key |
+| `folder`, `site`, `subject` | string | `site` is `G`, `R`, or `unknown` |
+| `view` | string | `A4C` throughout |
+| `frame_index`, `n_frames` | int32 | order within the recording |
+| `height`, `width` | int32 | native resolution |
+| `has_mask`, `gt_dense` | bool | GT presence / dense-annotation regime |
+| `gt_source` | string | `site_sparse`, `label_all_frame_filled`, `none` |
+| `mask_filled_from_contour` | bool | mask was reconstructed from an outline |
+| `label_remapped` | bool | `{5→1, 6→4}` applied |
+| `video_truncated` | bool | source label volume was truncated |
+| `group_id` | string | **split on this** — ties near-duplicate videos |
+| `deid_blanked_rows` | int32 | height of the zeroed header band |
+| `split` | string | `train` (single split) |
+
+## Provenance
+
+Retrieved from Kaggle `xiaoweixumedicalai/cardiacudc-dataset` (version 1,
+2023-10-30), 7-part split zip, 4,515,920,293 bytes, extracting to 658 NIfTI
+files / 4,547,904,911 bytes. Archive CRC verified before conversion.
+
+## Licence and attribution
+
+Released under the **Apache License, Version 2.0**, as declared by the dataset
+authors on the source Kaggle record. (The GraphEcho *code* repository is
+MIT-licensed — a separate grant covering the code, not this data.)
+
+```
+This dataset is a re-hosted and reprocessed copy of "cardiacUDC_dataset"
+(a.k.a. CardiacUDA), created by Xiaowei Xu et al., originally released at
+https://www.kaggle.com/datasets/xiaoweixumedicalai/cardiacudc-dataset
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use
+this file except in compliance with the License. You may obtain a copy at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, the dataset is
+distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND.
+
+Modifications by MedOtter, per Apache-2.0 section 4(b): conversion from NIfTI to
+per-frame PNG in parquet; contour masks polygon-filled; two volumes' stray label
+values remapped; one truncated source volume partially salvaged; frame
+orientation normalised; a fixed-height header band zeroed on every frame.
+See "What this release changes from source" above.
+```
+
+Please cite:
+
+```bibtex
+@inproceedings{yang2023graphecho,
+  title     = {GraphEcho: Graph-Driven Unsupervised Domain Adaptation for
+               Echocardiogram Video Segmentation},
+  author    = {Yang, Jiewen and Ding, Xinpeng and Zheng, Ziyang and
+               Xu, Xiaowei and Li, Xiaomeng},
+  booktitle = {Proceedings of the IEEE/CVF International Conference on
+               Computer Vision (ICCV)},
+  pages     = {11878--11887},
+  year      = {2023}
+}
+```