International Journal of Computer Vision

, Volume 105, Issue 2, pp 155–170

Teichmüller Shape Descriptor and Its Application to Alzheimer’s Disease Study

  • Wei Zeng
  • Rui Shi
  • Yalin Wang
  • Shing-Tung Yau
  • Xianfeng Gu
  • Alzheimer’s Disease Neuroimaging Initiative
Article

DOI: 10.1007/s11263-012-0586-8

Cite this article as:
Zeng, W., Shi, R., Wang, Y. et al. Int J Comput Vis (2013) 105: 155. doi:10.1007/s11263-012-0586-8

Abstract

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.

Keywords

Teichmüller spaceConformal weldingShape analysis

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Wei Zeng
    • 1
  • Rui Shi
    • 2
  • Yalin Wang
    • 3
  • Shing-Tung Yau
    • 4
  • Xianfeng Gu
    • 2
  • Alzheimer’s Disease Neuroimaging Initiative
  1. 1.Florida International UniversityMiamiUSA
  2. 2.State University of New York at Stony BrookStony BrookUSA
  3. 3.Arizona State UniversityTempeUSA
  4. 4.Harvard UniversityCambridgeUSA