Mitosis Domain Generalization Challenge 2025 (MIDOG)ยถ

Welcome to the MICCAI 2025 edition of the Mitosis Domain Generalization Challenge (MIDOG).


Why this challenge mattersยถ

Mitotic figures are a key biomarker in tumor grading โ€” yet detecting and classifying them reliably remains one of the most difficult tasks in digital pathology. Current AI models often fail when faced with the variability found in clinical samples: staining artifacts, inflammation, necrosis, or unseen scanners.

MIDOG 2025 addresses this by testing algorithms not just in ideal conditions, but across diverse, challenging, and unpredictable domains โ€” bringing us closer to clinical robustness.


Whatโ€™s new in 2025?ยถ

This year's challenge introduces two tracks, each addressing critical gaps in current AI capabilities:

Track 1 โ€“ Robust Mitosis Detectionยถ

Detect mitotic figures not only in curated regions of interest (ROIs) โ€” as in previous challenges โ€” but also in:

  • Adverse tissue regions (necrosis, inflammation, staining artifacts)
  • Randomly selected tissue crops from whole slide images (WSIs)

This simulates the real-world deployment scenario where no region is guaranteed to be "clean."
๐Ÿ‘‰ Learn more

Track 2 โ€“ Atypical Mitosis Classificationยถ

Detected mitoses must now be subclassified into:

  • Normal mitotic figures
  • Atypical mitotic figures โ€” which are independent markers of tumor malignancy and patient prognosis

This is a clinically important, yet understudied, task.
๐Ÿ‘‰ Learn more


Datasetsยถ

We provide a large, diverse training dataset from multiple domains with expert-verified annotations, following the high standards of previous MIDOG editions.
๐Ÿ“„ Details on dataset access


Timelineยถ

Date Milestone
โœ… March 25 Launch of challenge website
โœ… April 8 Training data & dataset description released
โณ August 15 Preliminary evaluation set submission opens
โณ August 31 Submission deadline for Docker container + 2-page abstract
๐Ÿ Sept 23 Announcement of results at MICCAI 2025

๐Ÿ’ก Join us!ยถ

MIDOG 2025 is more than a challenge โ€” itโ€™s a step toward deployable AI in oncology. We invite researchers, developers, and clinicians to help push the boundaries of what AI can truly achieve in cancer diagnostics.

๐Ÿ‘ฅ Join the discussion and ask questions on our Discord:
https://discord.gg/xEuqXjMqTk

Together, letโ€™s make mitosis detection reliable, explainable, and clinically useful.