Mitosis Domain Generalization Challenge 2025 (MIDOG)

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


Why this challenge matters

Mitotic figures are a key biomarker in tumor grading — 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 — bringing us closer to clinical robustness.


What’s new in 2025?

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

Track 1 – Robust Mitosis Detection

Detect mitotic figures not only in curated regions of interest (ROIs) — as in previous challenges — 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."
👉 Learn more

▶️ Introduction video

Track 2 – Atypical Mitosis Classification

Detected mitoses must now be subclassified into:

  • Normal mitotic figures
  • Atypical mitotic figures — which are independent markers of tumor malignancy and patient prognosis

This is a clinically important, yet understudied, task.
👉 Learn more

▶️ Introduction video


Datasets

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

How To Submit

Please find more details on how to submit on this page.

We provide two docker templates, including baseline algorithms: - Track 1: github link - Track 2: github link


Timeline

Date Milestone
✅ March 25 Launch of challenge website
✅ April 8 Training data & dataset description released
✅ July 30 Baseline methods & docker templates released
⏳ August 15 Preliminary evaluation set submission opens
⏳ August 31 Submission deadline for Docker container + 2-page abstract
🏁 Sept 23 Announcement of results at MICCAI 2025

💡 Join us!

MIDOG 2025 is more than a challenge — it’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.

👥 Join the discussion and ask questions on our Discord:
https://discord.gg/xEuqXjMqTk

Together, let’s make mitosis detection reliable, explainable, and clinically useful.