Teichmöller shape space theory and its application to brain morphometry.

  • Wang Y
  • Dai W
  • Gu X
 et al. 
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Abstract

Here we propose a novel method to compute Teichmiiller 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.

Author-supplied keywords

  • Algorithms
  • Brain
  • Brain: anatomy & histology
  • Humans
  • Image Enhancement
  • Image Enhancement: methods
  • Image Interpretation, Computer-Assisted
  • Image Interpretation, Computer-Assisted: methods
  • Imaging, Three-Dimensional
  • Imaging, Three-Dimensional: methods
  • Magnetic Resonance Imaging
  • Magnetic Resonance Imaging: methods
  • Pattern Recognition, Automated
  • Pattern Recognition, Automated: methods
  • Reproducibility of Results
  • Sensitivity and Specificity

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  • SCOPUS: 2-s2.0-84863022209
  • PUI: 358940273
  • SGR: 84863022209
  • PMID: 20426105

Authors

  • Yalin Wang

  • Wei Dai

  • Xianfeng Gu

  • Tony F Chan

  • Shing-Tung Yau

  • Arthur W Toga

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