To participate, you have to agree to the following rules:
- Submission is in the form of docker containers, as we can’t allow access to the test images during the competition. You will be given a template docker container to use for this.
- Participants are requested to publish a brief (approx. 2 pages) description of their method and results on a preprint site (such as arxiv.org, medrxiv.org) together with their submission. We do provide a template (double column, IEEE style) for this. There is no explicit page limit for that description, but it has to include a conclusive description of the approach of the participating team.
- This challenge features two tracks/tasks, and participants can decide if they participate in one of them or both:
- In the task 1 (mitosis detection without additional data), the use of additional data (as in: other microscopy data sets) is not permitted. This includes using models that were pre-trained on other microscopy data sets or using models trained on other microscopy datasets to generate own annotation data (e.g., instance segmentation data). Using models trained or pre-trained on general-purpose data sets (MS Coco, ImageNet) is allowed.
- In the task 2 (mitosis detection with additional data), the use of additional data sets is permitted, given that these are publicly available without conditions to all participants. If you want to use additional labels to publicly available data, please read our blog post addressing this topic.
- Training data is licensed as CC BY-NC-ND (Attribution-NonCommercial-NoDerivs), i.e. everyone (also non-participants of the challenge) are free to use the training data set in their respective work, given attribution in the publication.
- Researchers belonging to the institutes of the organizers are not allowed to participate to avoid potential conflict of interest.
Publication policy
- Participants may publish papers including their official performance on the challenge data set, given proper reference of the challenge. There is no embargo time in that regard.
- We aim to publish a summary of the challenge in a peer-reviewed journal. Participating teams are free to publish their own results in a separate publication.