A model of volumetric shape for the analysis of longitudinal Alzheimer's disease data

Authors:
Xinyang Liu;Xiuwen Liu;Yonggang Shi;Paul Thompson;Washington Mio
Affiliations:
Department of Mathematics, Florida State University, Tallahasse, FL;Department of Computer Science, Florida State University, Tallahasse, FL;Laboratory of NeuroImaging, UCLA School of Medicine, Los Angeles, CA;Laboratory of NeuroImaging, UCLA School of Medicine, Los Angeles, CA;Department of Mathematics, Florida State University, Tallahasse, FL
Venue:
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Year:
2010

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Abstract

We develop a multi-scale model of shape based on a volumetric representation of solids in 3D space. A signed energy function (SEF) derived from the model is designed to quantify the magnitude of regional shape changes that correlate well with local shrinkage and expansion. The methodology is applied to the analysis of longitudinal morphological data representing hippocampal volumes extracted from one-year repeat magnetic resonance scans of the brain of 381 subjects collected by the Alzheimer's Disease Neuroimaging Initiative.We first establish a strong correlation between the SEFs and hippocampal volume loss over a one-year period and then use SEFs to characterize specific regions where hippocampal atrophy over the one-year period differ significantly among groups of normal controls and subjects with mild cognitive impairment and Alzheimer's disease.