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MICCAI
2009
Springer

Multivariate Tensor-Based Brain Anatomical Surface Morphometry via Holomorphic One-Forms

12 years 7 months ago
Multivariate Tensor-Based Brain Anatomical Surface Morphometry via Holomorphic One-Forms
Abstract. Here we introduce multivariate tensor-based surface morphometry using holomorphic one-forms to study brain anatomy. We computed new statistics from the Riemannian metric tensors that retain the full information in the deformation tensor fields. We introduce two different holomorphic one-forms that induce different surface conformal parameterizations. We applied this framework to 3D MRI data to analyze hippocampal surface morphometry in Alzheimer's Disease (AD; 26 subjects), lateral ventricular surface morphometry in HIV/AIDS (19 subjects) and cortical surface morphometry in Williams Syndrome (WS; 80 subjects). Experimental results demonstrated that our method powerfully detected brain surface abnormalities. Multivariate statistics on the local tensors outperformed other TBM methods including analysis of the Jacobian determinant, the largest eigenvalue, or the pair of eigenvalues, of the surface Jacobian matrix.
Yalin Wang, Tony F. Chan, Arthur W. Toga, Paul M.
Added 05 Mar 2010
Updated 08 Mar 2010
Type Conference
Year 2009
Where MICCAI
Authors Yalin Wang, Tony F. Chan, Arthur W. Toga, Paul M. Thompson
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