Post-doc: Image Analytics in Prostate Histology
This project is in the field of medical image analysis applied to prostate histology. The treatment of prostate cancer patients is a complex, multidisciplinary task. Clinical decision making can be supported by combining quantitative information from various diagnostic inputs. One of these inputs is histology information provided by a pathologist after a needle biopsy. The advent of digital pathology which is facilitated by the technology of whole slide scanning has opened the way for using computer algorithms to extract quantitative information from scanned tissue sections.
The goal of the post-doctoral project is to develop new methods for image analysis of scanned and digitised tissue sections. The resulting quantitative information is then later delivered to clinicians for incorporation into decision-making models. Specifically, the goal is to apply both classical machine learning approaches and novel deep learning methods to detect and quantify so-called cribriform and intraductal carcinoma in the scanned prostate needle biopsies.
The research will be performed at the Department of Imaging Physics in the Faculty of Applied Sciences of Delft University of Technology. The project is a collaboration with the Erasmus Medical Centre and is supported by the Dutch Technology Foundation STW, the Dutch Cancer Foundation (KWF), and Philips Research. The candidate must hold a PhD in Computer Science, Biomedical Engineering, Physics or Electrical Engineering, with a thesis topic that is relevant to the project. In particular we are looking for candidates with experience in medical image analysis. Excellent analytical skills and a mindset geared towards cooperation with clinicians and towards application of the technology are essential.
This job comes from a partnership with Science Magazine and