| --- |
| license: other |
| license_name: sliver07-research-only |
| license_link: https://sliver07.grand-challenge.org/Rules/ |
| task_categories: |
| - image-segmentation |
| tags: |
| - medical |
| - ct |
| - liver |
| - segmentation |
| - sliver07 |
| - 3d |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: preview |
| data_files: |
| - split: train |
| path: preview/train-* |
| - split: test |
| path: preview/test-* |
| dataset_info: |
| config_name: preview |
| features: |
| - name: patient_id |
| dtype: string |
| - name: official_split |
| dtype: string |
| - name: num_slices |
| dtype: int32 |
| - name: image |
| dtype: image |
| - name: mask |
| dtype: image |
| - name: overlay |
| dtype: image |
| splits: |
| - name: train |
| num_bytes: 5705343.0 |
| num_examples: 20 |
| - name: test |
| num_bytes: 2790343.0 |
| num_examples: 10 |
| download_size: 8499887 |
| dataset_size: 8495686.0 |
| --- |
| |
| # SLIVER07 — MICCAI 2007 Liver Segmentation Challenge (re-mirror) |
|
|
| Re-host of the **SLIVER07** training + test releases from the |
| [Zenodo open-access mirror](https://zenodo.org/records/2597908), restructured |
| into the same `dataset/case_XXXXX/` + `train.jsonl` layout we use for |
| KiTS23 / KiPA22 / AbdomenCT1K so a single `Base3DDataset` subclass can load it. |
|
|
| ## Composition |
|
|
| | Split | Cases | With mask | |
| |-------|------:|----------:| |
| | train | 20 | yes | |
| | test | 10 | **no** (GT held server-side at sliver07.grand-challenge.org) | |
|
|
| `case_00000`..`case_00019` are the 20 training volumes (liver-orig001..020 in the |
| upstream naming) with paired ground-truth liver masks. `case_00020`..`case_00029` |
| are the 10 test volumes (liver-orig001..010) — the masks are withheld by the |
| challenge organizers for online scoring. Use the train split for benchmarking. |
|
|
| ## File layout |
|
|
| ``` |
| dataset/case_00000/ |
| imaging.mhd # MetaImage header (ElementDataFile = imaging.raw) |
| imaging.raw # binary CT volume |
| segmentation.mhd # MetaImage header (ElementDataFile = segmentation.raw) |
| segmentation.raw # binary 0/1 liver mask |
| ... |
| dataset/case_00029/ # test cases have only imaging.{mhd,raw} |
| train.jsonl |
| test.jsonl |
| README.md |
| ``` |
|
|
| `train.jsonl` / `test.jsonl` list one entry per case with `image`, `mask`, |
| `label`, `modality`, `dataset`, `official_split`, `patient_id` keys. Image/mask |
| paths are prefixed with `data/nii/SLIVER07/` so they slot directly into the |
| EasyMedSeg `Base3DDataset.HF_JSONL_PREFIX` convention. `mask` is `null` for |
| test entries. |
|
|
| ## Mask labels |
|
|
| CT integer labels: |
|
|
| | Value | Class | |
| |-------|------------| |
| | 0 | background | |
| | 1 | liver | |
|
|
| Single binary class — the official SLIVER07 GT is a single curated reference |
| mask per volume (verified by a radiologist). |
|
|
| ## CT voxel intensity |
|
|
| Raw HU values are preserved (MET_SHORT element type for images). Per-volume |
| spacing varies (0.5–5 mm slice spacing, 0.54–0.86 mm in-plane); read from each |
| `.mhd` header rather than assuming a fixed spacing. |
| |
| ## License |
| |
| This mirror inherits the SLIVER07 challenge terms, which permit research use |
| only and forbid commercial use or redistribution to non-registered parties. |
| See https://sliver07.grand-challenge.org/Rules/ for the canonical license. |
| The full upstream `license.txt` is reproduced at the repo root. |
| |
| Cite the canonical paper: |
| |
| ```bibtex |
| @article{heimann2009comparison, |
| title = {Comparison and evaluation of methods for liver segmentation from CT datasets}, |
| author = {Heimann, Tobias and van Ginneken, Bram and Styner, Martin A. and others}, |
| journal = {IEEE Transactions on Medical Imaging}, |
| volume = {28}, |
| number = {8}, |
| pages = {1251--1265}, |
| year = {2009}, |
| doi = {10.1109/TMI.2009.2013851} |
| } |
| ``` |
| |
