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2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (2008)
Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-7
Sheila Krishna , Department of Neurology, UCLA School of Medicine, USA
Nancy Sicotte , Department of Neurology, UCLA School of Medicine, USA
Yonggang Shi , Lab of Neuro Imaging, UCLA School of Medicine, USA
Arthur W. Toga , Lab of Neuro Imaging, UCLA School of Medicine, USA
Rongjie Lai , Department of Mathematics, UCLA, USA
Ivo Dinov , Lab of Neuro Imaging, UCLA School of Medicine, USA
ABSTRACT
In this paper we propose a novel approach of computing skeletons of robust topology for simply connected surfaces with boundary by constructing Reeb graphs from the eigen-functions of an anisotropic Laplace-Beltrami operator. Our work brings together the idea of Reeb graphs and skeletons by incorporating a flux-based weight function into the Laplace-Beltrami operator. Based on the intrinsic geometry of the surface, the resulting Reeb graph is pose independent and captures the global profile of surface geometry. Our algorithm is very efficient and it only takes several seconds to compute on neuroanatomical structures such as the cingulate gyrus and corpus callosum. In our experiments, we show that the Reeb graphs serve well as an approximate skeleton with consistent topology while following the main body of conventional skeletons quite accurately.
INDEX TERMS
CITATION
Sheila Krishna, Nancy Sicotte, Yonggang Shi, Arthur W. Toga, Rongjie Lai, Ivo Dinov, "Anisotropic Laplace-Beltrami eigenmaps: Bridging Reeb graphs and skeletons", 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 00, no. , pp. 1-7, 2008, doi:10.1109/CVPRW.2008.4563018
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