---
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}
}
```