Liver Tumor Segmentation Challenge Dataset
A challenge dataset for developing automatic segmentation algorithms for liver tumors in CT scans, used in conjunction with ISBI 2017 and MICCAI 2017 conferences.
Score
30
User Rating
3.0
Free/Trial Support
Not Supported
Starting Price
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Last Updated
Aug 04, 2026
Overview
What is Liver Tumor Segmentation Challenge Dataset?
The Liver Tumor Segmentation Challenge (LiTS) is a dataset and competition aimed at encouraging researchers to develop automatic segmentation algorithms for liver lesions in contrast-enhanced abdominal CT scans. It includes training and test data from various clinical sites worldwide.
What is Liver Tumor Segmentation Challenge Dataset used for?
Top Features
- 130 CT scans for training
- 70 CT scans for testing
- Evaluation of liver segmentation and tumor burden estimation
- Open leaderboard for submissions
- Workshops at ISBI 2017 and MICCAI 2017
How to use Liver Tumor Segmentation Challenge Dataset?
Register to access the dataset, download the data after approval, participate in the challenge by submitting segmentation results, and potentially contribute to a joint journal paper if among the top performers.
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Pros & Cons
Pros
- High-quality medical imaging data
- Encourages AI research in healthcare
- Opportunity for publication in high-impact journals
- Free to access and participate
Cons
- Limited to CT scan data
- Requires approval for data download
- No ongoing updates after challenge periods
Use Cases
- Developing AI models for liver tumor segmentation
- Academic research in medical imaging
- Benchmarking segmentation algorithms
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