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Latest research posts

An overview of my latest research posts. Most of these posts are linked to my PhD-research in computational pathology and prostate cancer. View all tech posts.

To improve prostate cancer detection and grading algorithms, we required a system that could precisely outline epithelial tissue. Our main idea was that such a system could automatically refine coarse annotations made by human annotators or other deep learning systems; for example in our project on automated Gleason grading. At...

100-word summary: The Gleason score is the most important prognostic marker for prostate cancer patients but suffers from significant inter-observer variability. We developed a fully automated deep learning system to grade prostate biopsies. The system was developed using 5834 biopsies from 1243 patients. A semi-automatic labeling technique was used to...

During the joint conferences of the IEEE International Conference on the Internet-of-Things Design and Implementation (IoTDI) (website) and the IEEE International Conference on Cloud Engineering (IC2E) (website) I presented my work on indoor localisation and SLAM: The indoor localisation problem is more complex than just finding whereabouts of users. Finding...

A key problem (or challenge) within smart spaces is indoor localization: making estimates of users’ whereabouts. Without such information, systems are unable to react on the presence of users or, sometimes even more important, their absence. This can range from simply turning the lights on when someone enters a room...