Maschenka Balkenhol will defend her thesis titled 'Tissue-based biomarker assessment for predicting prognosis of triple negative breast cancer: the additional value of artifical intelligence' on the 15th of September at 12.30. Her defense can be followed via live stream. 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.