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The cerebral stroke is a major cause for death and disability. Clinical diagnosis, therapy, and research of stroke can considerably benefit from modern image acquisition methods, which enable a detailed analysis of cerebral blood vessel anatomy as well as an examination of macrovascular and tissue blood flow dynamics. However, visual screening of these datasets can be complex and time-consuming due to the vast amount of data. This article provides an overview of a dissertation, which addresses the problem of an automatic combined analysis and visualization of high-resolution 3D and spatiotemporal (4D) image sequences from the same patient to support diagnosis, treatment decision, and research of cerebrovascular diseases. Therefore, automatic methods for the cerebrovascular segmentation, analysis of the cerebral blood flow and tissue perfusion, as well as the combined quantitative analysis and visualization of the vessel morphology and blood flow dynamics were developed. Apart from a potential clinical application, the developed methods have already proven useful in multiple clinical research studies.

Model-based analysis of cerebrovascular diseases combining 3D and 4D MRA datasets