These are the datasets relevant in the context of MIDOG 2025:
- AMi-Br Dataset:
Bertram, C.A. et al. (2025). Histologic Dataset of Normal and Atypical Mitotic Figures on Human Breast Cancer (AMi-Br). In: Palm, C., et al. Bildverarbeitung für die Medizin 2025. BVM 2025. Informatik aktuell. Springer Vieweg, Wiesbaden. [bibtex] - MIDOG25 Atypical Dataset:
Weiss, V., Banerjee, S., Donovan, T., Conrad, T., Klopfleisch, R., Ammeling, J., Kaltenecker, C., Hirling, D., Veta, M., Stathonikos, N., Horvath, P., Breininger, K., Aubreville, M., & Bertram, C. (2025). A dataset of atypical vs normal mitoses classification for MIDOG – 2025 [Data set]. Zenodo. 10.5281/zenodo.15188326 [bibtex] - MIDOG++ Dataset:
Aubreville, M., Wilm, F., Stathonikos, N., Breininger, K., Donovan, T. A., Jabari, S., … & Bertram, C. A. (2023). A comprehensive multi-domain dataset for mitotic figure detection. Scientific data, 10(1), 484. 10.1038/s41597-023-02327-4 [bibtex] - MITOS_WSI_CMC Dataset:
Aubreville, M., Bertram, C. A., Donovan, T. A., Marzahl, C., Maier, A., & Klopfleisch, R. (2020). A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research. Scientific data, 7(1), 417. 10.1038/s41597-020-00756-z [bibtex] - MITOS_WSI_CCMCT Dataset:
Bertram, C.A., Aubreville, M., Marzahl, C. et al. A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor. Sci Data 6, 274 (2019). https://doi.org/10.1038/s41597-019-0290-4 [bibtex] - AtNorM-Br Dataset:
Banerjee, S., Weiss, V., Donovan, T. A., Fick, R. H., Conrad, T., Ammeling, J., … & Bertram, C. A. (2025). Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation. arXiv preprint arXiv:2506.21444. [bibtex]