The course provides students with knowledge of several generally useful advanced algorithms. Topics include Randomized algorithms, String-matching algorithms, Divide & Conquer, Dynamic programming, Greedy algorithms, Graph algorithms, and more.
The course covers the fundamental concepts and methodologies of medical image computing and image analysis and relates those to clinical applications in diagnosis, therapy and intervention. The aim is to provide an overview of the different areas, such as image processing, registration and segmentation, with an emphasis on understanding the theoretical and practical aspects of various methods. The necessary skills will be taught that enable students to work and conduct research in medical image computing.
The group projects are an integral part of the HiPEDS CDT programme and its ambition to deliver valuable resources for outreach activities. The project work enables CDT students to be capable of integrating and innovating across multiple layers of the system development stack, and to acquire creativity, communication, team management and presentation skills.
2016: Project website
2014: News article