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

doi:10.1007/978-3-642-04271-3_17

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 proceeding › Conference contribution

15 Scopus citations

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 language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings
Pages	133-140
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-04271-3_17
State	Published - 2009
Externally published	Yes
Event	12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom Duration: Sep 20 2009 → Sep 24 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	5762 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
Country/Territory	United Kingdom
City	London
Period	9/20/09 → 9/24/09

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-04271-3_17

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 Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings (PART 2 ed., 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 et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. 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 proceeding › Conference 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 Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. PART 2 edn, 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 Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. PART 2 ed. 2009. p. 133-140. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-04271-3_17

Wang, Yalin ; Dai, Wei ; Gu, Xianfeng et al. / Teichmüller shape space theory and its application to brain morphometry. Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. 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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abstract = "Here we propose a novel method to compute Teichm{\"u}ller 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 Poincar{\'e} 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 Teichm{\"u}ller coordinates for lateral ventricular surfaces extracted from their 3D MRI scans.",

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Teichmüller shape space theory and its application to brain morphometry

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