After CAMELYON, there is now PANDA, our new challenge on prostate cancer grading in collaboration with Kaggle and Karolinska Institutet. Our aim is to crowdsource the best possible solution to help pathologists better diagnose and treat patients. Read more →
Computational Pathology Group
The Computational Pathology Group develops, validates and deploys novel medical image analysis methods based on deep learning technology.
Vacancies & Student projects
Aim of the presently proposed ‘proof of concept‘ study is to develop digital pattern recognition algorithms (more specifically: deep neural networks) for the extraction of morphological features from scanned H&E stained tissue sections from TNBC which are indicative for the risk of recurrence.
The goal of this project is to develop a deep learning model that can detect and classify the different types of artifacts observed in whole slide images.