Dr. Alexander Leemans, UMC Utrecht/Imaging Division, lecturer
Dr. Kenneth Gilhuijs, UMC Utrecht/Imaging Division, lecturer
Renée Allebrandi, MA (course registration)
This course covers the full roadmap from basic to more advanced techniques that are commonly used in medical image processing. You will learn how to analyse concrete medical questions that arise from medical images, and that can be solved by mathematical analysis of CT, MRI and X-ray. We will take you from theory to design of computer-aided diagnosis systems and Radiomics systems. Examples of such systems are those that automatically detect tumors in CT and MRI scans, that automatically detect micro-aneurysms in retinal images, or that estimate the prognosis of breast-cancer patients based on imaging features that cannot be picked up by the human eye. Topics include segmentation (dynamic programming, active contours, level sets), image registration, mathematical morphology, texture analysis, pattern recognition (feature spaces, classifiers; support-vector machines and random forests). During the lectures we will provide small practical assignments using a voting system. A computer practicum will be provided to get hands-on experience with the different techniques. In addition, individual assignments are provided consisting of actual problems that were encountered in medical images.
Literature/study material used
Book: Image Processing, Analysis, and Machine vision (Sonka, Hlavac, Boyle), as well as handout materials.
At least 2 weeks before start of the course via the study guide