International Journal of Computer Vision

, Volume 105, Issue 2, pp 155–170 | Cite as

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


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.


Teichmüller space Conformal welding Shape analysis 



This work was supported by NIH R01EB007530 0A1, NSF IIS0916286, NSF CCF0916235, NSF CCF0830550, NSF III0713145, and ONR N000140910228, NSFC 61202146, and SDC BS2012DX014. Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Amorfix Life Sciences Ltd.; AstraZeneca; Bayer Healthcare; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the AD Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129, K01 AG030514, and the Dana Foundation. This work has been supported by NSF CCF-0448399, NSF DMS-0528363, NSF DMS-0626223, NSF CCF-0830550, NSF IIS-0916286, NSF CCF-1081424, and ONR N000140910228. Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database ( As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at:


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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

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