Teichmüller shape descriptor and its application to alzheimer's disease study

Wei Zeng, Rui Shi, Yalin Wang, Shing Tung Yau, Xianfeng Gu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


We propose a novel method to apply Teichmüller space theory to study the signature of a family of nonintersecting closed 3D curves on a general genus zero closed surface. Our algorithm provides an efficient method to encode both global surface and local contour shape information. The signature - Teichmüller shape descriptor - is computed by surface Ricci flow method, which is equivalent to solving an elliptic partial differential equation on surfaces and is numerically stable. We propose to apply the new signature to analyze abnormalities in brain cortical morphometry. Experimental results with 3D MRI data from Alzheimer's disease neuroimaging initiative (ADNI) dataset [152 healthy control subjects versus 169 Alzheimer's disease (AD) patients] demonstrate the effectiveness of our method and illustrate its potential as a novel surface-based cortical morphometry measurement in AD research.

Original languageEnglish (US)
Pages (from-to)155-170
Number of pages16
JournalInternational Journal of Computer Vision
Issue number2
StatePublished - Nov 2013


  • Conformal welding
  • Shape analysis
  • Teichmüller space

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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