Computational Pathology Group
The Computational Pathology Group develops, validates and deploys novel medical image analysis methods based on deep learning technology.
Vacancies & Student projects
Crossing the boundaries: machine learning for pancreatic cancer across radiology, pathology and genetics (PANCAIM)
We are offering three PhD positions to apply machine learning to varying diagnostic modality to improve treatment for pancreatic cancer patients
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.
Development of a deep learning algorithm that can classify the different types of artifacts in whole slide images.Read more →