LiTS17 (Liver Tumor Segmentation Challenge 2017)
LiTS17 is a liver tumor segmentation benchmark. The data and segmentations are provided by various clinical sites around the world. The training data set contains 130 CT scans.
The segmentation classes are: Background, Liver and Tumor.
Raw data
Key stats
| Modality | Vision (radiology, CT scans) |
| Task | Segmentation (3 classes) |
| Data size | train: 15GB (53.66 GB uncompressed) |
| Image dimension | ~500 x 512 x 512 |
| Files format | .nii ("NIFTI") images |
| Number of scans | 130 (58638 slices) |
| Splits in use | train (82.17%) / val (17.83%) |
Splits
We use the following random split:
| Splits | Train | Validation |
|---|---|---|
| #Scans | 107 (82.31%) | 23 (17.69%) |
Organization
The training data are organized as follows:
Training Batch 1 # Train images part 1
├── segmentation-0.nii # Semantic labels for volume 0
├── segmentation-1.nii # Semantic labels for volume 1
├── ...
├── volume-0.nii # CT-Scan 0
├── volume-1.nii # CT-Scan 1
└── ...
Training Batch 2 # Train images part 2
├── segmentation-28.nii # Semantic labels for volume 28
├── segmentation-29.nii # Semantic labels for volume 29
├── ...
├── volume-28.nii # CT-Scan 28
├── volume-29.nii # CT-Scan 29
└── ...
Download and preprocessing
The LiTS dataset can be downloaded from the official
LiTS competition page.
The training split comes into two .zip files, namely Training_Batch1.zip
and Training_Batch2.zip, which should be extracted and merged.