CAMELYON16

The goal of this challenge is to evaluate new and existing algorithms for automated detection of cancer metastasis in digitized lymph node tissue sections. Two large datasets from both the Radboud University Medical Center and the University Medical Center Utrecht are provided.

CAMELYON17

Automated detection and classification of breast cancer metastases in whole-slide images of histological lymph node sections. This task has high clinical relevance and would normally require extensive microscopic assessment by pathologists.

ICIAR 2018

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

PAIP2021

PAIP 2021 Challenge; Perineural invasion in multiple organ cancer (colon, prostate and pancreatobiliary tract)

WSSS4LUAD

The WSSS4LUAD dataset contains over 10,000 patches of lung adenocarcinoma from whole slide images from Guangdong Provincial People's Hospital and TCGA with image-level annotations. The goal of this challenge is to perform semantic segmentation for differentiating three important types of tissues in the WSIs of lung adenocarcinoma, including cancerous epithelial region, cancerous stroma region and normal region. Paticipants have to use image-level annotations to give pixel-level prediction.

TIGER

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

AGGC22

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.

The LEOPARD Challenge

MONKEY challenge: Detection of inflammation in kidney biopsies

MONKEY (Machine-learning for Optimal detection of iNflammatory cells in KidnEY)