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ICCV
2009
IEEE

Shape analysis with multivariate tensor-based morphometry and holomorphic differentials

8 years 9 months ago
Shape analysis with multivariate tensor-based morphometry and holomorphic differentials
In this paper, we propose multivariate tensor-based surface morphometry, a new method for surface analysis, using holomorphic differentials; we also apply it to study brain anatomy. Differential forms provide a natural way to parameterize 3D surfaces, but the multivariate statistics of the resulting surface metrics have not previously been investigated. We computed new statistics from the Riemannian metric tensors that retain the full information in the deformation tensor fields. We present the canonical holomorphic one-forms with improved numerical accuracy and computational efficiency. We applied this framework to 3D MRI data to analyze hippocampal surface morphometry in Alzheimer's Disease (AD; 12 subjects), lateral ventricular surface morphometry in HIV/AIDS (11 subjects) and biomarkers in lateral ventricles in HIV/AIDS (11 subjects). Experimental results demonstrated that our method powerfully detected brain surface abnormalities. Multivariate statistics on the local tensors...
Yalin Wang, Tony F. Chan, Arthur W. Toga, Paul M.
Added 18 Feb 2011
Updated 18 Feb 2011
Type Journal
Year 2009
Where ICCV
Authors Yalin Wang, Tony F. Chan, Arthur W. Toga, Paul M. Thompson
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