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Teichmüller shape space theory and its application to brain morphometry

  • T.F. Chan
  • , W. Dai
  • , X. Gu
  • , P.M. Thompson
  • , A.W. Toga
  • , Y. Wang
  • , S.T. Yau

Research output: Contribution to conferenceConference Paperpeer-review

Abstract

Here we propose a novel method to compute Teichmüller shape space based shape index to study brain morphometry. Such a shape index is intrinsic, and invariant under conformal transformations, rigid motions and scaling. We conformally map a genus-zero open boundary surface to the Poincaré disk with the Yamabe flow method. The shape indices that we compute are the lengths of a special set of geodesics under hyperbolic metric. Tests on longitudinal brain imaging data were used to demonstrate the stability of the derived feature vectors. In leave-one-out validation tests, we achieved 100% accurate classification (versus only 68% accuracy for volume measures) in distinguishing 11 HIV/AIDS individuals from 8 healthy control subjects, based on Teichmüller coordinates for lateral ventricular surfaces extracted from their 3D MRI scans. © 2009 Springer-Verlag.
Original languageEnglish
DOIs
Publication statusPublished - 2009
EventLecture Notes in Computer Science -
Duration: 1 Jan 20091 Jan 2009

Conference

ConferenceLecture Notes in Computer Science
Period1/01/091/01/09

ISBNs

['3642042708']

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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