cancer classification computational pathology computer vision deep learning digital pathology grand-challenge.org histopathology imaging life sciences machine learning medical image computing medical imaging
This dataset contains the training data for the Machine learning for Optimal detection of iNflammatory cells in the KidnEY or MONKEY challenge. The MONKEY challenge focuses on the automated detection and classification of inflammatory cells, specifically monocytes and lymphocytes, in kidney transplant biopsies using Periodic acid-Schiff (PAS) stained whole-slide images (WSI). It contains 80 WSI, collected from 4 different pathology institutes, with annotated regions of interest. For each WSI up to 3 different PAS scans and one IHC slide scan are available. This dataset and challenge support the development of AI models that can aid in the diagnostic process, reduce pathologists’ workload, and improve patient outcomes in renal transplantation.
As required
CC BY-NC-SA 4.0
https://monkey.grand-challenge.org/
Radboud University Medical Center
See all datasets managed by Radboud University Medical Center.
MONKEY was accessed on DATE from https://registry.opendata.aws/monkey.
arn:aws:s3:::monkey-trainingus-west-2aws s3 ls --no-sign-request s3://monkey-training/