diff --git a/README.md b/README.md
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index 0000000000000000000000000000000000000000..52a809ac7592486b1b703bbbf377e4c37378e3ca
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+---
+license: cc-by-4.0
+task_categories:
+- image-segmentation
+tags:
+- medical
+- cta
+- ct
+- aorta
+- aortic-dissection
+- vascular
+- 3d
+pretty_name: Aortic Dissection (Graz) - true/false lumen CTA
+size_categories:
+- n<1K
+---
+
+# Aortic Dissection (Graz) - CTA with true / false lumen expert annotations
+
+Re-host of **"Aortic Dissection Dataset and Segmentations"**
+([figshare 10.6084/m9.figshare.22269091](https://doi.org/10.6084/m9.figshare.22269091),
+CC BY 4.0) - 40 **type-B aortic dissection** CTA volumes collected in clinical
+routine 2005-2021 across the Medical University of Graz regional hospital
+network, with expert **true-lumen** and **false-lumen** annotations.
+
+> Mayer C, Pepe A, Hossain S, Karner B, Arnreiter M, Kleesiek J, Schmid J,
+> Janisch M, Fuchsjaeger M, Deutschmann H, Zimpfer D, Egger J, Maechler H.
+> *Type B Aortic Dissection CTA Collection with True and False Lumen Expert
+> Annotations for the Development of AI-based Algorithms.*
+> **Scientific Data 11, 596 (2024).** doi:10.1038/s41597-024-03284-2
+
+Ethics: Medical University of Graz EK-34-161 ex 21/22; consent waived
+(retrospective), head and face cropped for anonymisation.
+
+## Contents
+
+| | |
+|---|---|
+| Modality | CTA, arterial phase (**not** ECG-gated) |
+| Cases | 40, one volume each |
+| Classes | `0` background, `1` true lumen, `2` false lumen |
+| Split | **none** - single cohort of 40 (`split="train"` for all rows) |
+| Shape | mostly 512x512xZ; in-plane spacing 0.525-0.965 mm, through-plane 1.25-3.0 mm |
+| Foreground | TL 125,516-659,055 voxels; FL 25,242-496,428 voxels; **no empty masks** |
+
+**There is no thrombus class.** Per the paper, "clearly thrombosed sections have
+not been segmented"; calcifications and atherosclerotic changes are likewise
+excluded. Ambiguous dark regions judged to be late-filling artifact were
+segmented *as lumen*. If you need a thrombus label, see ImageTBAD instead.
+
+## Layout
+
+```
+dataset/ctaNNs/ctaNNs.nrrd           image, int16 HU - byte-identical to figshare
+               truelumenNN.seg.nrrd  true lumen,  uint8 {0,1}
+               falselumenNN.seg.nrrd false lumen, uint8 {0,1}
+               maskNN.nrrd           merged {0=bg, 1=TL, 2=FL}
+               meshNN.stl            surface mesh - byte-identical to figshare
+original_masks/ctaNNs/*.seg.nrrd     untouched source masks (~13 MB total)
+train.jsonl                          40 rows (schema below)
+```
+
+`train.jsonl` per row: `case_id`, `case_num`, `image`, `mask`,
+`mask_true_lumen`, `mask_false_lumen`, `mesh`, `original_mask_*`, `shape`,
+`spacing_mm`, `coarse_axis`, `tl_voxels`, `fl_voxels`, `tl_volume_ml`,
+`fl_volume_ml`, `tl_fl_overlap_voxels`, `fl_label_value_raw`,
+`resampled_to_image_grid`, `annotator_tier`, `split`.
+
+## What was normalised here (and why)
+
+Everything below is flagged per-case in `train.jsonl`, and the untouched source
+masks ship under `original_masks/`.
+
+1. **False-lumen masks binarised to `{0,1}`.** 17 of 40 cases store the false
+   lumen with **label value 2**, the other 23 with 1 - cases
+   `4, 5, 11, 12, 13, 14, 15, 16, 17, 18, 22, 25, 26, 30, 35, 36, 38`. Code
+   doing `mask == 1` against the raw files silently drops those 17 false
+   lumens. Original value kept in `fl_label_value_raw`.
+2. **Case 40 masks resampled onto the image grid.** As shipped, case 40's masks
+   sit on a grid rotated ~6.85 deg about Z (512x1103x187 @0.545 mm) while its
+   image is axis-aligned (512x512x401 @0.602 mm) - index-wise pairing raises
+   `IndexError`. Nearest-neighbour world-space resampling retains **100.01% /
+   100.04%** of physical volume, and mean HU inside the resampled masks is
+   **409 HU (TL) / 339 HU (FL)**, i.e. contrast-filled arterial lumen and in
+   line with the other 39 cases. Flagged by `resampled_to_image_grid`.
+   Every other case's masks already match their image exactly.
+3. **Merged `maskNN.nrrd` added**, painted TL first then FL, so **FL wins
+   ties**. Ties are negligible: 16 of 40 cases overlap by 1-106 voxels, at most
+   **0.028%** of the TL-or-FL union - flap-boundary jitter, not a nested
+   structure. The two binaries remain available if you prefer to fan out.
+
+Deliberately **not** changed: no reorientation, no resampling of the other 39
+cases, no intensity windowing, original filenames kept.
+
+## Gotchas
+
+- **Key masks off the FILENAME, never the segment name.** Internal Slicer names
+  are inconsistent: case 2's true lumen is called `artery`, case 19's *false*
+  lumen is also called `artery`, and elsewhere you find `true lumen 5`,
+  `true_lumen`, `truelumen`, `True Lumen neu`, `flase lumen`, `False_Lumen`.
+- **Cases 19 and 20 are sagittally reformatted**: the coarse 1.5 mm axis is
+  NRRD axis 0, not axis 2 (all other 38 cases have it at axis 2). A hard-coded
+  z-slicer emits ~950 thin reformats instead of ~240 native slices. Use
+  `coarse_axis` from `train.jsonl`.
+- **No official split.** Group any split you make on `case_id`; one patient owns
+  exactly one volume, so a plain case-level split is safe.
+- **Anisotropic**, up to 3.0 mm through-plane.
+- The images are the anonymised, head/face-cropped reconstructions. The
+  separate `raw CTs.zip` on figshare is **not** mirrored here on purpose: its
+  case 24 is a *different reconstruction* (776x776x101 oblique @0.625/0.625/2.4
+  mm) that does **not** align with the masks.
+
+## Annotation provenance - one tier, all of it gold
+
+All 40 masks were seeded semi-automatically (local thresholding / Grow Cut,
+fill-between-slices interpolation, or region growing - the paper's Table 2 gives
+the per-case method), then given **2-3 hours of manual slice-by-slice
+paint/erase**, because the paper reports the semi-automated results "were not
+precise enough for AI applications". A radiologist then checked every case.
+
+`annotator_tier` records who did the manual work: 15 cases (`1-10, 26, 27, 28,
+29, 39`, the paper's Table-1 nabla marker) by a medical student, the other 25 by
+cardiac-surgery residents. The paper marks these deliberately *to show there is
+no difference between software users* - so **all 40 are gold and none should be
+filtered**; the column is there for stratification only.
+
+**Measured vs published volumes.** The `tl_volume_ml` / `fl_volume_ml` values
+here are measured directly from the mask files. They reproduce the paper's
+Table 2 to within +/-1% for 35 of 40 cases (most within 0.1%), which
+independently confirms the image-mask pairing and the binarisation. Five cases
+(`5, 6, 7, 32, 36`) disagree in the **true-lumen column only**; in three of them
+the paper's TL cell exactly equals its FL cell, which looks like a transcription
+slip. Each mask file contains exactly one correctly-named segment, so this is a
+table artifact, not extra structures in the data. Trust the values here.
+
+## Related datasets / leakage
+
+**No patient overlap with [`MedOtter/SegA`](https://huggingface.co/datasets/MedOtter/SegA)**
+(the AVT collection: KiTS 20 + RIDER 18 + Dongyang 18 - US and Chinese cohorts).
+The two share *authors* (Pepe, Egger), not patients, and AVT's few incidental
+dissection cases carry only a single binary aortic-vessel-tree mask, not
+lumen labels. No overlap with AortaSeg24 (Univ. of Florida), ImageTBAD
+(Guangdong), TotalSegmentator (Basel), or any TCIA collection. No
+cross-reference ID to other datasets exists; `case_id` (`cta01`-`cta40`) joins
+only to Tables 1 and 2 of the paper.
+
+## License
+
+**CC BY 4.0** - redistribution and commercial use permitted with attribution.
+Cite the Scientific Data paper above and the figshare record.
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+{"case_id": "cta01", "case_num": 1, "image": "dataset/cta01s/cta01s.nrrd", "mask": "dataset/cta01s/mask01.nrrd", "mask_true_lumen": "dataset/cta01s/truelumen01.seg.nrrd", "mask_false_lumen": "dataset/cta01s/falselumen01.seg.nrrd", "mesh": "dataset/cta01s/mesh01.stl", "original_mask_true_lumen": "original_masks/cta01s/truelumen01.seg.nrrd", "original_mask_false_lumen": "original_masks/cta01s/falselumen01.seg.nrrd", "shape": [512, 512, 508], "spacing_mm": [0.679688, 0.679688, 1.5], "coarse_axis": 2, "tl_voxels": 266736, "fl_voxels": 177263, "tl_volume_ml": 184.84, "fl_volume_ml": 122.84, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta02", "case_num": 2, "image": "dataset/cta02s/cta02s.nrrd", "mask": "dataset/cta02s/mask02.nrrd", "mask_true_lumen": "dataset/cta02s/truelumen02.seg.nrrd", "mask_false_lumen": "dataset/cta02s/falselumen02.seg.nrrd", "mesh": "dataset/cta02s/mesh02.stl", "original_mask_true_lumen": "original_masks/cta02s/truelumen02.seg.nrrd", "original_mask_false_lumen": "original_masks/cta02s/falselumen02.seg.nrrd", "shape": [512, 512, 260], "spacing_mm": [0.757812, 0.757812, 2.0], "coarse_axis": 2, "tl_voxels": 148839, "fl_voxels": 188427, "tl_volume_ml": 170.95, "fl_volume_ml": 216.42, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta03", "case_num": 3, "image": "dataset/cta03s/cta03s.nrrd", "mask": "dataset/cta03s/mask03.nrrd", "mask_true_lumen": "dataset/cta03s/truelumen03.seg.nrrd", "mask_false_lumen": "dataset/cta03s/falselumen03.seg.nrrd", "mesh": "dataset/cta03s/mesh03.stl", "original_mask_true_lumen": "original_masks/cta03s/truelumen03.seg.nrrd", "original_mask_false_lumen": "original_masks/cta03s/falselumen03.seg.nrrd", "shape": [512, 512, 433], "spacing_mm": [0.796875, 0.796875, 1.5], "coarse_axis": 2, "tl_voxels": 228345, "fl_voxels": 400352, "tl_volume_ml": 217.5, "fl_volume_ml": 381.34, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta04", "case_num": 4, "image": "dataset/cta04s/cta04s.nrrd", "mask": "dataset/cta04s/mask04.nrrd", "mask_true_lumen": "dataset/cta04s/truelumen04.seg.nrrd", "mask_false_lumen": "dataset/cta04s/falselumen04.seg.nrrd", "mesh": "dataset/cta04s/mesh04.stl", "original_mask_true_lumen": "original_masks/cta04s/truelumen04.seg.nrrd", "original_mask_false_lumen": "original_masks/cta04s/falselumen04.seg.nrrd", "shape": [512, 512, 252], "spacing_mm": [0.691406, 0.691406, 2.0], "coarse_axis": 2, "tl_voxels": 318226, "fl_voxels": 193742, "tl_volume_ml": 304.25, "fl_volume_ml": 185.23, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta05", "case_num": 5, "image": "dataset/cta05s/cta05s.nrrd", "mask": "dataset/cta05s/mask05.nrrd", "mask_true_lumen": "dataset/cta05s/truelumen05.seg.nrrd", "mask_false_lumen": "dataset/cta05s/falselumen05.seg.nrrd", "mesh": "dataset/cta05s/mesh05.stl", "original_mask_true_lumen": "original_masks/cta05s/truelumen05.seg.nrrd", "original_mask_false_lumen": "original_masks/cta05s/falselumen05.seg.nrrd", "shape": [512, 457, 316], "spacing_mm": [0.729, 0.729, 2.0], "coarse_axis": 2, "tl_voxels": 191932, "fl_voxels": 170895, "tl_volume_ml": 204.0, "fl_volume_ml": 181.64, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta06", "case_num": 6, "image": "dataset/cta06s/cta06s.nrrd", "mask": "dataset/cta06s/mask06.nrrd", "mask_true_lumen": "dataset/cta06s/truelumen06.seg.nrrd", "mask_false_lumen": "dataset/cta06s/falselumen06.seg.nrrd", "mesh": "dataset/cta06s/mesh06.stl", "original_mask_true_lumen": "original_masks/cta06s/truelumen06.seg.nrrd", "original_mask_false_lumen": "original_masks/cta06s/falselumen06.seg.nrrd", "shape": [512, 512, 452], "spacing_mm": [0.871094, 0.871094, 1.25], "coarse_axis": 2, "tl_voxels": 240082, "fl_voxels": 223743, "tl_volume_ml": 227.72, "fl_volume_ml": 212.22, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta07", "case_num": 7, "image": "dataset/cta07s/cta07s.nrrd", "mask": "dataset/cta07s/mask07.nrrd", "mask_true_lumen": "dataset/cta07s/truelumen07.seg.nrrd", "mask_false_lumen": "dataset/cta07s/falselumen07.seg.nrrd", "mesh": "dataset/cta07s/mesh07.stl", "original_mask_true_lumen": "original_masks/cta07s/truelumen07.seg.nrrd", "original_mask_false_lumen": "original_masks/cta07s/falselumen07.seg.nrrd", "shape": [512, 512, 393], "spacing_mm": [0.691406, 0.691406, 1.5], "coarse_axis": 2, "tl_voxels": 345643, "fl_voxels": 150118, "tl_volume_ml": 247.85, "fl_volume_ml": 107.64, "tl_fl_overlap_voxels": 6, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta08", "case_num": 8, "image": "dataset/cta08s/cta08s.nrrd", "mask": "dataset/cta08s/mask08.nrrd", "mask_true_lumen": "dataset/cta08s/truelumen08.seg.nrrd", "mask_false_lumen": "dataset/cta08s/falselumen08.seg.nrrd", "mesh": "dataset/cta08s/mesh08.stl", "original_mask_true_lumen": "original_masks/cta08s/truelumen08.seg.nrrd", "original_mask_false_lumen": "original_masks/cta08s/falselumen08.seg.nrrd", "shape": [512, 512, 431], "spacing_mm": [0.789062, 0.789062, 1.5], "coarse_axis": 2, "tl_voxels": 415305, "fl_voxels": 25242, "tl_volume_ml": 387.87, "fl_volume_ml": 23.57, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta09", "case_num": 9, "image": "dataset/cta09s/cta09s.nrrd", "mask": "dataset/cta09s/mask09.nrrd", "mask_true_lumen": "dataset/cta09s/truelumen09.seg.nrrd", "mask_false_lumen": "dataset/cta09s/falselumen09.seg.nrrd", "mesh": "dataset/cta09s/mesh09.stl", "original_mask_true_lumen": "original_masks/cta09s/truelumen09.seg.nrrd", "original_mask_false_lumen": "original_masks/cta09s/falselumen09.seg.nrrd", "shape": [512, 512, 310], "spacing_mm": [0.78125, 0.78125, 2.0], "coarse_axis": 2, "tl_voxels": 125516, "fl_voxels": 104964, "tl_volume_ml": 153.22, "fl_volume_ml": 128.13, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta10", "case_num": 10, "image": "dataset/cta10s/cta10s.nrrd", "mask": "dataset/cta10s/mask10.nrrd", "mask_true_lumen": "dataset/cta10s/truelumen10.seg.nrrd", "mask_false_lumen": "dataset/cta10s/falselumen10.seg.nrrd", "mesh": "dataset/cta10s/mesh10.stl", "original_mask_true_lumen": "original_masks/cta10s/truelumen10.seg.nrrd", "original_mask_false_lumen": "original_masks/cta10s/falselumen10.seg.nrrd", "shape": [512, 512, 341], "spacing_mm": [0.742188, 0.742188, 2.0], "coarse_axis": 2, "tl_voxels": 231382, "fl_voxels": 68584, "tl_volume_ml": 254.91, "fl_volume_ml": 75.56, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "student", "split": "train"}
+{"case_id": "cta11", "case_num": 11, "image": "dataset/cta11s/cta11s.nrrd", "mask": "dataset/cta11s/mask11.nrrd", "mask_true_lumen": "dataset/cta11s/truelumen11.seg.nrrd", "mask_false_lumen": "dataset/cta11s/falselumen11.seg.nrrd", "mesh": "dataset/cta11s/mesh11.stl", "original_mask_true_lumen": "original_masks/cta11s/truelumen11.seg.nrrd", "original_mask_false_lumen": "original_masks/cta11s/falselumen11.seg.nrrd", "shape": [512, 512, 177], "spacing_mm": [0.677, 0.677, 3.0], "coarse_axis": 2, "tl_voxels": 134496, "fl_voxels": 64326, "tl_volume_ml": 184.93, "fl_volume_ml": 88.45, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta12", "case_num": 12, "image": "dataset/cta12s/cta12s.nrrd", "mask": "dataset/cta12s/mask12.nrrd", "mask_true_lumen": "dataset/cta12s/truelumen12.seg.nrrd", "mask_false_lumen": "dataset/cta12s/falselumen12.seg.nrrd", "mesh": "dataset/cta12s/mesh12.stl", "original_mask_true_lumen": "original_masks/cta12s/truelumen12.seg.nrrd", "original_mask_false_lumen": "original_masks/cta12s/falselumen12.seg.nrrd", "shape": [512, 512, 330], "spacing_mm": [0.742188, 0.742188, 2.0], "coarse_axis": 2, "tl_voxels": 285723, "fl_voxels": 113555, "tl_volume_ml": 314.78, "fl_volume_ml": 125.1, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta13", "case_num": 13, "image": "dataset/cta13s/cta13s.nrrd", "mask": "dataset/cta13s/mask13.nrrd", "mask_true_lumen": "dataset/cta13s/truelumen13.seg.nrrd", "mask_false_lumen": "dataset/cta13s/falselumen13.seg.nrrd", "mesh": "dataset/cta13s/mesh13.stl", "original_mask_true_lumen": "original_masks/cta13s/truelumen13.seg.nrrd", "original_mask_false_lumen": "original_masks/cta13s/falselumen13.seg.nrrd", "shape": [512, 512, 319], "spacing_mm": [0.652344, 0.652344, 2.0], "coarse_axis": 2, "tl_voxels": 325661, "fl_voxels": 443590, "tl_volume_ml": 277.17, "fl_volume_ml": 377.54, "tl_fl_overlap_voxels": 56, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta14", "case_num": 14, "image": "dataset/cta14s/cta14s.nrrd", "mask": "dataset/cta14s/mask14.nrrd", "mask_true_lumen": "dataset/cta14s/truelumen14.seg.nrrd", "mask_false_lumen": "dataset/cta14s/falselumen14.seg.nrrd", "mesh": "dataset/cta14s/mesh14.stl", "original_mask_true_lumen": "original_masks/cta14s/truelumen14.seg.nrrd", "original_mask_false_lumen": "original_masks/cta14s/falselumen14.seg.nrrd", "shape": [512, 512, 214], "spacing_mm": [0.64, 0.64, 2.0], "coarse_axis": 2, "tl_voxels": 154208, "fl_voxels": 159119, "tl_volume_ml": 126.33, "fl_volume_ml": 130.35, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta15", "case_num": 15, "image": "dataset/cta15s/cta15s.nrrd", "mask": "dataset/cta15s/mask15.nrrd", "mask_true_lumen": "dataset/cta15s/truelumen15.seg.nrrd", "mask_false_lumen": "dataset/cta15s/falselumen15.seg.nrrd", "mesh": "dataset/cta15s/mesh15.stl", "original_mask_true_lumen": "original_masks/cta15s/truelumen15.seg.nrrd", "original_mask_false_lumen": "original_masks/cta15s/falselumen15.seg.nrrd", "shape": [512, 512, 475], "spacing_mm": [0.742188, 0.742188, 1.5], "coarse_axis": 2, "tl_voxels": 203586, "fl_voxels": 178431, "tl_volume_ml": 168.22, "fl_volume_ml": 147.43, "tl_fl_overlap_voxels": 106, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta16", "case_num": 16, "image": "dataset/cta16s/cta16s.nrrd", "mask": "dataset/cta16s/mask16.nrrd", "mask_true_lumen": "dataset/cta16s/truelumen16.seg.nrrd", "mask_false_lumen": "dataset/cta16s/falselumen16.seg.nrrd", "mesh": "dataset/cta16s/mesh16.stl", "original_mask_true_lumen": "original_masks/cta16s/truelumen16.seg.nrrd", "original_mask_false_lumen": "original_masks/cta16s/falselumen16.seg.nrrd", "shape": [512, 512, 194], "spacing_mm": [0.625, 0.625, 3.0], "coarse_axis": 2, "tl_voxels": 155428, "fl_voxels": 94216, "tl_volume_ml": 182.14, "fl_volume_ml": 110.41, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta17", "case_num": 17, "image": "dataset/cta17s/cta17s.nrrd", "mask": "dataset/cta17s/mask17.nrrd", "mask_true_lumen": "dataset/cta17s/truelumen17.seg.nrrd", "mask_false_lumen": "dataset/cta17s/falselumen17.seg.nrrd", "mesh": "dataset/cta17s/mesh17.stl", "original_mask_true_lumen": "original_masks/cta17s/truelumen17.seg.nrrd", "original_mask_false_lumen": "original_masks/cta17s/falselumen17.seg.nrrd", "shape": [512, 512, 460], "spacing_mm": [0.691406, 0.691406, 1.5], "coarse_axis": 2, "tl_voxels": 356048, "fl_voxels": 496428, "tl_volume_ml": 255.31, "fl_volume_ml": 355.97, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta18", "case_num": 18, "image": "dataset/cta18s/cta18s.nrrd", "mask": "dataset/cta18s/mask18.nrrd", "mask_true_lumen": "dataset/cta18s/truelumen18.seg.nrrd", "mask_false_lumen": "dataset/cta18s/falselumen18.seg.nrrd", "mesh": "dataset/cta18s/mesh18.stl", "original_mask_true_lumen": "original_masks/cta18s/truelumen18.seg.nrrd", "original_mask_false_lumen": "original_masks/cta18s/falselumen18.seg.nrrd", "shape": [512, 512, 328], "spacing_mm": [0.742188, 0.742188, 2.0], "coarse_axis": 2, "tl_voxels": 291919, "fl_voxels": 255443, "tl_volume_ml": 321.6, "fl_volume_ml": 281.42, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta19", "case_num": 19, "image": "dataset/cta19s/cta19s.nrrd", "mask": "dataset/cta19s/mask19.nrrd", "mask_true_lumen": "dataset/cta19s/truelumen19.seg.nrrd", "mask_false_lumen": "dataset/cta19s/falselumen19.seg.nrrd", "mesh": "dataset/cta19s/mesh19.stl", "original_mask_true_lumen": "original_masks/cta19s/truelumen19.seg.nrrd", "original_mask_false_lumen": "original_masks/cta19s/falselumen19.seg.nrrd", "shape": [241, 560, 961], "spacing_mm": [1.5, 0.621094, 0.621025], "coarse_axis": 0, "tl_voxels": 659055, "fl_voxels": 41813, "tl_volume_ml": 381.31, "fl_volume_ml": 24.19, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta20", "case_num": 20, "image": "dataset/cta20s/cta20s.nrrd", "mask": "dataset/cta20s/mask20.nrrd", "mask_true_lumen": "dataset/cta20s/truelumen20.seg.nrrd", "mask_false_lumen": "dataset/cta20s/falselumen20.seg.nrrd", "mesh": "dataset/cta20s/mesh20.stl", "original_mask_true_lumen": "original_masks/cta20s/truelumen20.seg.nrrd", "original_mask_false_lumen": "original_masks/cta20s/falselumen20.seg.nrrd", "shape": [218, 512, 945], "spacing_mm": [1.5, 0.703125, 0.702918], "coarse_axis": 0, "tl_voxels": 258466, "fl_voxels": 108272, "tl_volume_ml": 191.62, "fl_volume_ml": 80.27, "tl_fl_overlap_voxels": 4, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta21", "case_num": 21, "image": "dataset/cta21s/cta21s.nrrd", "mask": "dataset/cta21s/mask21.nrrd", "mask_true_lumen": "dataset/cta21s/truelumen21.seg.nrrd", "mask_false_lumen": "dataset/cta21s/falselumen21.seg.nrrd", "mesh": "dataset/cta21s/mesh21.stl", "original_mask_true_lumen": "original_masks/cta21s/truelumen21.seg.nrrd", "original_mask_false_lumen": "original_masks/cta21s/falselumen21.seg.nrrd", "shape": [512, 512, 319], "spacing_mm": [0.742188, 0.742188, 2.0], "coarse_axis": 2, "tl_voxels": 330066, "fl_voxels": 398483, "tl_volume_ml": 363.63, "fl_volume_ml": 439.0, "tl_fl_overlap_voxels": 65, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
+{"case_id": "cta22", "case_num": 22, "image": "dataset/cta22s/cta22s.nrrd", "mask": "dataset/cta22s/mask22.nrrd", "mask_true_lumen": "dataset/cta22s/truelumen22.seg.nrrd", "mask_false_lumen": "dataset/cta22s/falselumen22.seg.nrrd", "mesh": "dataset/cta22s/mesh22.stl", "original_mask_true_lumen": "original_masks/cta22s/truelumen22.seg.nrrd", "original_mask_false_lumen": "original_masks/cta22s/falselumen22.seg.nrrd", "shape": [512, 512, 222], "spacing_mm": [0.781, 0.781, 3.0], "coarse_axis": 2, "tl_voxels": 152340, "fl_voxels": 90102, "tl_volume_ml": 278.76, "fl_volume_ml": 164.88, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 2, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
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+{"case_id": "cta31", "case_num": 31, "image": "dataset/cta31s/cta31s.nrrd", "mask": "dataset/cta31s/mask31.nrrd", "mask_true_lumen": "dataset/cta31s/truelumen31.seg.nrrd", "mask_false_lumen": "dataset/cta31s/falselumen31.seg.nrrd", "mesh": "dataset/cta31s/mesh31.stl", "original_mask_true_lumen": "original_masks/cta31s/truelumen31.seg.nrrd", "original_mask_false_lumen": "original_masks/cta31s/falselumen31.seg.nrrd", "shape": [512, 512, 400], "spacing_mm": [0.761719, 0.761719, 1.5], "coarse_axis": 2, "tl_voxels": 237329, "fl_voxels": 271867, "tl_volume_ml": 206.55, "fl_volume_ml": 236.61, "tl_fl_overlap_voxels": 0, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
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+{"case_id": "cta33", "case_num": 33, "image": "dataset/cta33s/cta33s.nrrd", "mask": "dataset/cta33s/mask33.nrrd", "mask_true_lumen": "dataset/cta33s/truelumen33.seg.nrrd", "mask_false_lumen": "dataset/cta33s/falselumen33.seg.nrrd", "mesh": "dataset/cta33s/mesh33.stl", "original_mask_true_lumen": "original_masks/cta33s/truelumen33.seg.nrrd", "original_mask_false_lumen": "original_masks/cta33s/falselumen33.seg.nrrd", "shape": [512, 453, 450], "spacing_mm": [0.785156, 0.785156, 1.5], "coarse_axis": 2, "tl_voxels": 165333, "fl_voxels": 119041, "tl_volume_ml": 152.88, "fl_volume_ml": 110.08, "tl_fl_overlap_voxels": 1, "fl_label_value_raw": 1, "resampled_to_image_grid": false, "annotator_tier": "resident", "split": "train"}
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