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 achieve acceptable results on segmenting liver lesions.
With our challenge we encourage researchers to develop automatic segmentation algorithms to segment liver lesions in contrast-enhanced abdomen CT scans. The data and segmentations are provided by various clinical sites around the world. The challenge is organised in conjunction with ISBI 2017.
1. Register here to get access
2. Download the data after approval
3. Check our Google Groups and FAQ
5. Submit your results
6. Win the Challenge
The goal of this challenge is to automatically segment liver lesions in CT volumes. We evaluate only liver lesion segmentations and not liver segmentations.
However, to foster performance we provide liver masks during training time. During test time only the medical volumes not no liver mask will be available.
We will evaluate Dice, volumetric overlap (VO), relative volume difference (RVD), average symmetric surface distance (ASSD) and maximum symmetric surface distance (MSSD). Please have a look at our metrics notebook (soon available).
The top 10 participating teams and individuals will be invited to contribute to a joint journal paper describing and summarising the methods used and results found in this challenge. The paper will be submitted to a high-impact journal in the field no later than 6 months after the challenge. In order to be included in the joint journal paper the participants must send to the organisers or submit to arXiv a 4 page paper in appropriate LNCS latex describing their methods. The organisers will review the paper for sufficient detail to be able to understand and reproduce the method and hold the right to exclude participants from the joint journal paper in case their method description was not adequate.
Appropriate citation is to be made in scientific publications (journal publications, conference papers, technical reports, presentations at conferences and meetings) that use the data shared in this challenge. Currently, this citation must refer to this website, and later to the publication that will describe the results of this challenge. Teams must notify the organisers of the challenge about any publication that is (partly) based on the results or data published on this site, in order for us to maintain a list of publications associated with the challenge.
Creative Commons Licence This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Feel free to contact us if you have any questions or need clarification regarding the rules of the challenge or the licensing of the data.
Patrick Christ, Florian Ettlinger, Felix Gruen, Georgios Kassis, Fabian Lohöfer, Rickmer Braren & Bjoern Menze
Julian Holch, Felix Hofmann, Wieland Sommer & Volker Heinemann
Colin Jacobs, Gabriel Efrain HumpireMamani & Bram van Ginneken
Gabriel Chartrand, Eugene Vorontsov, An Tang, Michal Drozdza & Samuel Kadoury
Avi Ben-Cohen, Eyal Klang, Marianne M. Amitai, Eli Konen & Hayit Greenspan.
Johan Moreau, Alexandre Hostettler & Luc Soler
Refael Vivanti, Adi Szeskin, Naama Lev-Cohain, Jacob Sosna & Leo Joskowicz
If you have questions please have a look at our Google Group. If you encounter any issues during the submission process please have a look into the CodaLab Documentation.
Start: Dec. 1, 2016, midnight
Start: Jan. 15, 2017, midnight
Start: Feb. 15, 2017, midnight
Start: Feb. 22, 2017, midnight
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