Teichmüller Shape Descriptor and Its Application to Alzheimerr’s Diseasee Study
Wei Zeng, Rui Shi, Yalin Wang, Shing-Tung Yau, Xianfeng Gu
We propose a novel method to apply Teichmüller space theory to study the signature of a family of nonintersecting closed 3D curves on a general genus zero closed surface. Our algorithm provides an efficient method to encode both global surface and local contour shape information. The signature – Teichmüller shape descriptor – is computed by surface Ricci flow method, which is equivalent to solving an elliptic partial differential equation on surfaces and is numerically stable. We propose to apply the new signature to analyze abnormalities in brain corticalmorphometry.Experimental results with 3DMRI data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset (152 healthy control subjects versus 169 Alzheimer’s disease (AD) patients) demonstrate the effectiveness of our method and illustrate its potential as a novel surface-based cortical morphometry measurement in AD research.
Figures (click on each for a larger version):
- Zeng W, Shi R, Wang Y, Yau S-T, Gu X, ADNI Group, Teichmüller Shape Descriptor and Its Application to Alzheimer’s Disease Study, International Journal of Computer Vision, 2012, In Press.
- Y. Wang, X. Gu, T.F. Chan, and P.M. Thompson “ Shape Analysis with Conformal Invariants for Multiply Connected Domains and its Application to Analyzing Brain Morphology“, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Miami Beach, FL, USA, Jun. 2009