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Morphometric Analysis of 3D Surfaces: Application to Hippocampal Shape in Mild Cognitive Impairment

By Li Shen, Andrew Saykin, Tara Mchugh, John West, Laura Rabin, Heather Wishart, Moo K. Chung and Fillia Makedon

Abstract

A computational framework is presented for morphometric analysis of 3D surfaces that aims to localize regionally specific shape changes between groups of 3D objects. This framework integrates a set of powerful surface modeling and processing techniques, including the spherical harmonics (SPHARM) description for surface modeling, a quaternion-based method for 3D shape registration, heat kernel smoothing for increasing surface signal-tonoise ratio, and random fields theory for statistical inference on the surface. The effectiveness of this framework is demonstrated in a computational neuroscience application for identifying hippocampal shape changes in Mild Cognitive Impairment (MCI)

Topics: Shape analysis, surface modeling, heat kernel smoothing, Gaussian
Year: 2008
OAI identifier: oai:CiteSeerX.psu:10.1.1.134.3064
Provided by: CiteSeerX
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