Multivariate tensor-based brain anatomical surface morphometry via holomorphic one-forms

Yalin Wang, Tony F. Chan, Arthur W. Toga, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings
Pages337-344
Number of pages8
EditionPART 1
DOIs
StatePublished - 2009
Externally publishedYes
Event12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom
Duration: Sep 20 2009Sep 24 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5761 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
Country/TerritoryUnited Kingdom
CityLondon
Period9/20/099/24/09

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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