ANHIR

The challenge focuses on comparing the accuracy (using manually annotated landmarks) and the approximate speed of automatic non-linear registration methods for aligning microscopy images of multi-stained histology tissue samples.

RIADD (ISBI-2021)

Retinal Image Analysis for multi-Disease Detection

SegPC-2021

This challenge is positioned towards robust segmentation of cells which is the first stage to build such a tool for plasma cell cancer, namely, Multiple Myeloma (MM), which is a type of blood cancer.

NuCLS

Classification, Localization and Segmentation of nuclei in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad et al. 2021. arXiv:2102.09099 [cs.CV].

Breast Cancer Segmentation

Semantic segmentation of histologic regions in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. Bioinformatics. 2019. doi: 10.1093/bioinformatics/btz083

TIGER

Grand challenge on automate assessment of tumor infiltrating lymphocytes in digital pathology slides of triple negative and Her2-positive breast cancers

CoNIC 2022

Colon Nuclei Identification and Counting Challenge 2022

ACROBAT 2023

The ACROBAT challenge aims to advance the development of WSI registration algorithms that can align WSIs of IHC-stained breast cancer tissue sections to corresponding tissue regions that were stained with H&E. All WSIs originate from routine diagnostic workflows.

OCELOT 2023: Cell Detection from Cell-Tissue Interaction