Lecture: Prof. Bjoern Menze
External resources: Zoom video link, recorded lectures, other materials available in Moodle
Upon completion of the course, participants will be able to use computational models for extracting diagnostic information from different types of clinical image data sets. These data sets may provide information, for example, about blood perfusion or micro-structural tissue properties, about metabolic processes, or patterns of disease progression. The participants will understand the physiological concepts underlying the computational algorithms employed, and will know of advantages and shortcomings of different modeling strategies. This will allow them to analyze clinical imaging protocols with respect to the underlying physiological information, and to propose diagnostic algorithms that combine anatomical and physiological information of different imaging. A focus will be on applications from neuroimaging.
Due to the electronic teaching requirements of this semester, the format will differ a bit from previous years and from the module description. No coding exercises will take place, but a discussion and presentation of research papers instead.
Structure Macro:
Structure Micro:
Blood Perfusion:
Blood Neurokinetics:
Metabolism MRI:
Metabolism PET:
Disease Models (Tumor):
Disease Models (Population):
TeachingForm | |
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Title: | Computational Physiology for Medical Image Computing |
Professor: | Prof. Bjoern Menze |
Tutors: | TBA |
Type: | Lecture |
Information: | 2 + 2 SWS, 6 ECTS Credits (IN2319) |
Term: | 2020SoSe |
Abstract: |