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Rules:

  • All participants must form teams (even if the team is composed of a single participant), and each participant can only be a member of a single team.

  • Any individual participating with multiple or duplicate Grand Challenge profiles will be disqualified.

  • Anonymous participation is not allowed. To qualify for ranking on the validation/testing leaderboards, true names and affiliations [university, institute or company (if any), country] must be displayed accurately on verified Grand Challenge profiles, for all participants.

  • Members of all sponsoring or organizing entities (i.e. Radboud University Medical Center, University Medical Center Groningen, University of Copenhagen) can freely participate in the challenge, but are not eligible for awards or the final ranking in the testing phase.

  • This challenge only supports the submission of fully automated methods in Docker containers. It is not possible to submit semi-automated or interactive methods.

  • All Docker containers submitted to the challenge will be run offline (i.e., they will not have access to the internet and cannot download/upload any resources). All necessary resources (e.g., pre-trained weights) must be encapsulated in the submitted containers apriori.

  • Participants are allowed a maximum of 15 submissions during the Open Development Phase, with a restriction of 2 submissions per week.

  • Submissions will have a timeout limit of 5 minutes for processing a single case across all Phases.

  • During inference, participants will have access to a NVIDIA T4 GPU (16GB VRAM) by default. Only if a compelling justification is provided, they can request access to an NVIDIA A10G GPU (24GB VRAM) for solutions that require additional computational resources.

  • Participants competing for prizes can use pre-trained AI models based on computer vision and/or medical imaging datasets (e.g. ImageNet, Medical Segmentation Decathlon). They can also use external datasets to train their AI algorithms. However, such data and/or models must be published under a permissive license (within 3 months of the Open Development Phase deadline) to give all other participants a fair chance at competing on equal footing. They must also clearly state the use of external data in their submission, using the algorithm name [e.g., "LUNA25 Classification Model (trained w/ private data)"], algorithm page, and/or a supporting publication/URL.

  • Researchers and companies, interested in benchmarking their institutional AI models or products but not competing for prizes, can freely use private or unpublished external datasets to train their AI algorithms. They must clearly state the use of external data in their submission, using the algorithm name [e.g., "LUNA25 Classification Model (trained w/ private data)"], algorithm page, and/or a supporting publication/URL. They are not obligated to publish their AI models and/or datasets before or anytime after the submission.

  • To be eligible for prizes in the Closed Testing Phase, participants must submit a short scientific report on their methodology (2–3 pages) and we recommend (but do not enforce) to provide a link to a public Github repository with the source code of the algorithm. We take these measures to ensure the credibility and reproducibility of all proposed solutions and to promote open-source AI development.

  • Participants of the LUNA25 challenge, as well as non-participating researchers using the LUNA25 public training dataset, can publish their own results separately at any time. They do not have to adhere to any embargo period. While doing so, they are requested to cite the Study Protocol document (BIAS preregistration form for the LUNA25 challenge), which can be found at: https://zenodo.org/records/15094631. Once a study protocol and/or a challenge paper has been published, they are requested to refer to those publications instead.

  • Organizers of the LUNA25 challenge reserve the right to disqualify any participant or participating team at any time on grounds of unfair or dishonest practices.

  • All participants reserve the right to drop out of the LUNA25 challenge and forego any further participation. However, they will not be able to retract their prior submissions or any published results till that point in time.