Datasets:
Liver Tumor Segmentation Benchmark (LiTS)
License
CC BY-NC-SA 4.0
Creative Commons Attribution-NonCommercial-ShareAlike License
Citation
Paper BibTeX:
@article{bilic2023liver,
title={The liver tumor segmentation benchmark (lits)},
author={Bilic, Patrick and Christ, Patrick and Li, Hongwei Bran and Vorontsov, Eugene and Ben-Cohen, Avi and Kaissis, Georgios and Szeskin, Adi and Jacobs, Colin and Mamani, Gabriel Efrain Humpire and Chartrand, Gabriel and others},
journal={Medical image analysis},
volume={84},
pages={102680},
year={2023},
publisher={Elsevier}
}
Dataset description
The Liver Tumor Segmentation Benchmark (LiTS) was organized alongside ISBI 2017 and MICCAI 2017/2018 to advance liver and liver tumor segmentation in contrast-enhanced CT scans. It includes diverse cases from seven institutions worldwide and has served as a long-standing benchmark with ongoing public evaluation.
Competition homepage: https://competitions.codalab.org/competitions/17094
Number of CT volumes: 201
Contrast: Contrast-enhanced
CT body coverage: Abdomen
Does the dataset include any ground truth annotations?: Yes
Original GT annotation targets: Liver, lesion
Number of annotated CT volumes: 201
Annotator: Human
Acquisition centers: Collected from seven clinical sites globally, including (a) Rechts der Isar Hospital, the Technical University of Munich in Germany, (b) Radboud University Medical Center, the Netherlands, (c) Polytechnique Montréal and CHUM Research Center in Canada, (d) Sheba Medical Center in Israel, (e) the Hebrew University of Jerusalem in Israel, (f) Hadassah University Medical Center in Israel, and (g) IRCAD in France
Pathology/Disease: Primary liver tumors (e.g., hepatocellular carcinoma, cholangiocarcinoma) and secondary liver tumors (e.g., metastases from colorectal, breast, and lung cancers)
Original dataset download link:
Original dataset format: nifti
Note
LiTS test set ground truth remains private.