Teichmüller shape space theory and its application to brain morphometry

Yalin Wang, Wei Dai, Xianfeng Gu, Tony F. Chan, Shing Tung Yau, Arthur W. Toga, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages133-140
Number of pages8
Volume5762 LNCS
EditionPART 2
DOIs
StatePublished - 2009
Externally publishedYes
Event12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom
Duration: Sep 20 2009Sep 24 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5762 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
CountryUnited Kingdom
CityLondon
Period9/20/099/24/09

Fingerprint

Morphometry
Shape Space
Brain
Hyperbolic Metric
Conformal Transformation
Feature Vector
Imaging techniques
Geodesic
Lateral
Genus
Imaging
Scaling
Invariant
Motion
Zero
Demonstrate
Magnetic Resonance Imaging

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Wang, Y., Dai, W., Gu, X., Chan, T. F., Yau, S. T., Toga, A. W., & Thompson, P. M. (2009). Teichmüller shape space theory and its application to brain morphometry. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 5762 LNCS, pp. 133-140). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5762 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-04271-3_17

Teichmüller shape space theory and its application to brain morphometry. / Wang, Yalin; Dai, Wei; Gu, Xianfeng; Chan, Tony F.; Yau, Shing Tung; Toga, Arthur W.; Thompson, Paul M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5762 LNCS PART 2. ed. 2009. p. 133-140 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5762 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, Y, Dai, W, Gu, X, Chan, TF, Yau, ST, Toga, AW & Thompson, PM 2009, Teichmüller shape space theory and its application to brain morphometry. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 edn, vol. 5762 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5762 LNCS, pp. 133-140, 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, London, United Kingdom, 9/20/09. https://doi.org/10.1007/978-3-642-04271-3_17
Wang Y, Dai W, Gu X, Chan TF, Yau ST, Toga AW et al. Teichmüller shape space theory and its application to brain morphometry. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 ed. Vol. 5762 LNCS. 2009. p. 133-140. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-642-04271-3_17
Wang, Yalin ; Dai, Wei ; Gu, Xianfeng ; Chan, Tony F. ; Yau, Shing Tung ; Toga, Arthur W. ; Thompson, Paul M. / Teichmüller shape space theory and its application to brain morphometry. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5762 LNCS PART 2. ed. 2009. pp. 133-140 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
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