Affiliation:
1. Department of Radiology & Hotchkiss Brain Institute, Faculty of Medicine, University of Calgary
Abstract
Abstract
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.