The Liver Tumor Segmentation Benchmark (LiTS)
Technical University of Munich · Guangdong University of Foreign Studies · +62 more institutions
Abstract
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70…
Citation impact
- FWCI
- 83.22
- Percentile
- 100%
- References
- 169
Authors
109- PBPatrick Bilic
Technical University of Munich
- PFPatrick Ferdinand Christ
Technical University of Munich
- HLHongwei LiCorresponding
Guangdong University of Foreign Studies, University of Zurich, Quantitative BioSciences, Technical University of Munich
- EVEugene Vorontsov
Polytechnique Montréal
- ABAvi Ben-Cohen
Tel Aviv University
Topics & keywords
- Benchmark (surveying)
- Segmentation
- Computer science
- Artificial intelligence
- Medical physics
- Medicine
- Pattern recognition (psychology)
- Cartography