EXACT
A web-based collaboration toolset for algorithm-aided annotation of images with annotation version control.
Read more →Projects
Annotation software, datasets, and challenges we've built and released.
SlideRunner
A PyQt-based open source tool for massive cell annotations.
Read more →CATCH
A tumor tissue segmentation dataset comprising 350 whole slide images of seven different canine cutaneous tumors, complemented by 12,424 polygon annotations for 13 histologic classes.
Read more →MITOS_WSI_CMC
The currently largest dataset for breast cancer annotated on complete whole slide images. It contains 21 cases of canine breast cancer, labeled as the consensus of three experts.
Read more →MITOS_WSI_CCMCT
The largest dataset for mitosis on canine cutaneous mast cell tumor, and the largest dataset with verified mitotic figures (around 44k cells). Each cell has been labeled as a consensus of three pathologists.
Read more →TUPAC16_AL
A set of alternative labels for the TUPAC16 challenge auxiliary mitosis dataset. Our research paper shows that it's more complete and has a lower level of label noise.
Read more →EIPH
An inter-species cell detection dataset aimed at detecting pulmonary hemosiderophages in equine, human, and feline specimens.
Read more →Pan-tumor T-lymphocyte detection dataset
An immunohistochemistry dataset stained positive for CD3. It comprises 92 ROIs from four tumor indications with cell-level annotations for CD3+ cells, tumor cells, and other cells.
Read more →Multi-scanner SCC dataset
A subset of the CATCH dataset digitized with five different scanning systems. The images provide local correspondences useful for domain shift experiments and WSI registration.
Read more →FreeLeaf
FreeLeaf is a free online LateX editor, made for use in your lab.
Read more →MIDOG++
Extends the MIDOG 2021 and MIDOG 2022 challenge datasets. It comprises 503 ROIs of seven different tumor types with variable morphologic, laboratory, and scanner origins, with a total of 11,937 annotated mitotic figures.
Read more →QuiltCleaner
A representative selection of impurity annotations for images from the QUILT-1M dataset, complemented with predictions for the remainder of the dataset.
Read more →MIDOG Challenges
We organized the Mitosis Domain Generalization Challenge (MIDOG) at MICCAI in 2021, 2022, and 2025, with challenge report papers published in Medical Image Analysis.
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