Abstract
We segment and topologically classify brain vessel data obtained from magnetic resonance angiography (MRA). The segmentation is done adaptively and the classification by means of cubical homology, i.e. the computation of homology groups. In this way the number of connected components; (measured by H/sub 0/), the tunnels (given by H/sub 1/) and the voids (given by H/sub 2/) are determined, resulting in a topological characterization of the blood vessels.
Type
Publication
Proceedings of the 2002 International Conference on Image Processing, ICIP 2002, Rochester, New York, USA, September 22-25, 2002
Marc Niethammer
Professor of Computer Science
My research interests include image registration, image segmentation, shape analysis, machine learning, and biomedical applications.