ICIAR 2018

Can you develop a method for automatic detection of cancerous regions in breast cancer histology images?

DRIVE

Develop a system to automatically segment vessels in human retina fundus images.

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.

BreastPathQ: Cancer Cellularity Challenge 2019

SPIE-AAPM-NCI BreastPathQ:Cancer Circularity Challenge 2019: Participants will be tasked to develop an automated method for analyzing histology patches extracted from whole slide images and assign a score reflecting cancer cellularity for tumor burden assessment in each.

VerSe`19

Vertebrae labelling and segmentation on a spine dataset on an unprecedented 150 CT scans with voxel-level vertebral annotations.

Lymphocyte Assessment Hackathon

Lymphocyte Assessment Hackathon in conjunction with the MICCAI COMPAY 2019 Workshop on Computational Pathology

VerSe'20

Vertebrae labelling and segmentation on a multi-centre, multi-scanner, and anatomically-diverse CT dataset.

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

AIROGS

Artificial Intelligence for RObust Glaucoma Screening Challenge

CoNIC 2022

Colon Nuclei Identification and Counting Challenge 2022

BCNB

Early Breast Cancer Core-Needle Biopsy WSI Dataset

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.

MItosis DOmain Generalization Challenge 2022

Breast Cancer Immunohistochemical Image Generation Challenge

The Breast Cancer Immunohistochemical Image Generation Challenge aims to directly generate IHC-stained breast cancer histopathology images from HE-stained images.

PAIP 2023: TC prediction in pancreatic and colon cancer

Tumor cellularity prediction in pancreatic cancer (supervised learning) and colon cancer (transfer learning)