Publication Policy

To be eligible for final rankings,  participating teams must submit an algorithm description paper (no more than 4 pages). 
Please follow the format of the Springer Lecture Notes in Computer Science.
The paper should include the following aspects.

• Any usage of a public dataset—including pretraining or domain adaptation—should be explicitly disclosed in the solution paper submitted by the participating teams.

• Data preprocessing and augmentation

• Algorithm description

• Post-processing, if any, was applied

• Result analysis

• Link to the public code repository of the algorithm

Challenge Paper

Top teams will be invited to present their methods at the workshop.  Top teams will also be invited to collaborate with organizers to contribute to a challenge review paper, which could be potentially accepted by a leading medical image journal such as IEEE TMI, MIA, or similar. Top teams will be invited by the organizers based on the leaderboard ranks, the technical contributions of the solution, and the number of participants in the challenge.

All team members of invited teams will be eligible for co-authorship in the challenge paper. We appreciate and welcome all potential collaborators and value the contributions they bring. Participating teams are encouraged to publish their paper separately in academic journals or conference proceedings to disseminate their findings and contribute to the wider research community.