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.
About the author
Nils Daniel Forkert graduated with a Diploma in Computer Science with a specialization in image processing at the University of Hamburg, Germany, in 2009. He continued to study Medical Physics (distance learning course) at the Technical University of Kaiserslautern, Germany, and received his MSc degree in 2012. At the same time, he was working as researcher at the Department of Medical Informatics and Department of Computational Neuroscience at the University Hospital Hamburg-Eppendorf and received his PhD in 2013 from the Department of Informatics at the University of Hamburg. After that, he worked as a postdoctoral researcher at the Radiological Sciences Laboratory at Stanford University, USA. In November 2014, he was appointed as an Assistant Professor at the Department of Radiology at the University of Calgary, Canada.
Department of Radiology & Hotchkiss Brain Institute, Faculty of Medicine, University of Calgary
©2015 Walter de Gruyter Berlin/Boston
