Register a team of cSeg-2022

Terms of Participation:

The cSeg-2022 challenge is organized in the spirit of cooperative scientific progress. We do not claim any ownership or rights to the algorithms but we require anyone to respect the rules below. The following rules apply to those who register a team and/or download the data:

• The downloaded data or any data derived from these data are not redistributed under any circumstances.
• All information entered when registering a team, including the name of the contact person, the affiliation (institute, organization or company the team’s contact person works for) and the e-mail address must be complete and correct. In other words, anonymous registration is not allowed. The data provided will not be used for any purposes other than the cSeg-2022 competition. If you want to submit anonymously, for example because you want to submit your results to a conference that requires anonymous submission, please contact yuesun@med.unc.edu
• Data downloaded from this site may only be used for the purpose of preparing an entry to be submitted on this site. The data may not be used for other purposes in scientific studies and may not be used to train or develop other algorithms, including but not limited to algorithms used in commercial products.
• The segmentation results can be submitted 2 times, only the latest/best results will appear online. Tuning parameters for a just 0.001 improvement (Dice) is not encouraged.
• Results of your submission will only be published on the website when a document (e.g., a scientific paper) describing the method is provided. Please e-mail this document (or a link to it) to the organizers if you want your results to be published.
• If a commercial system is evaluated, no method description is necessary. But the system has to be publicly available and the exact name and version number have to be provided.
• The organizers of the challenge will check the method description before your results can be published on the website.
• Please make sure that whenever you use and/or refer to the cSeg-2022 datasets in your manuscripts, you should always cite https://tarheels.live/cseg2022/ and the following paper:

  Sun, Y., Wang, L., Gao, K. et al. Self-supervised learning with application for infant cerebellum segmentation and analysis. Nat Commun 14, 4717 (2023). https://doi.org/10.1038/s41467-023-40446-z  

• Evaluation of the segmentation results uploaded will be made publicly available on the cSeg-2022 website. By submitting your results, you grant us permission to publish our evaluation. Participating teams maintain full ownership and rights of their methods.
• Teams must notify the organizers of cSeg-2022 about any publication that is (partly) based on the results published on this site.