LiTS – Liver Tumor Segmentation Challenge (LiTS17)
Patrick Christ

LITS17 (262 files)
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Type: Dataset
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Bibtex:
@article{,
title= {LiTS – Liver Tumor Segmentation Challenge (LiTS17)},
keywords= {},
author= {Patrick Christ},
abstract= {The liver is a common site of primary (i.e. originating in the liver like hepatocellular carcinoma, HCC) or secondary (i.e. spreading to the liver like colorectal cancer) tumor development. Due to their heterogeneous and diffusive shape, automatic segmentation of tumor lesions is very challenging. Until now, only interactive methods achieved acceptable results segmenting liver lesions.

With our challenge we encourage researchers to develop automatic segmentation algorithms to segment liver lesions in contrast­-enhanced abdominal CT scans. The data and segmentations are provided by various clinical sites around the world. The training data set contains 130 CT scans and the test data set 70 CT scans. The challenge is organised in conjunction with ISBI 2017 and MICCAI 2017. For MICCAI 2017 we added tasks for liver segmentation and tumor burden estimation.

![](https://i.imgur.com/ia2qGlH.png)

![](https://i.imgur.com/eDN20ck.png)

Paper reference: https://arxiv.org/abs/1901.04056


},
terms= {},
license= {https://creativecommons.org/licenses/by-nc-nd/4.0/},
superseded= {},
url= {https://competitions.codalab.org/competitions/17094}
}


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