Hyperbolic harmonic mapping for constrained brain surface registration

Rui Shi, Wei Zeng, Zhengyu Su, Hanna Damasio, Zhonglin Lu, Yalin Wang, Shing Tung Yau, Xianfeng Gu

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

16 Citations (Scopus)

Abstract

Automatic computation of surface correspondence via harmonic map is an active research field in computer vision, computer graphics and computational geometry. It may help document and understand physical and biological phenomena and also has broad applications in biometrics, medical imaging and motion capture. Although numerous studies have been devoted to harmonic map research, limited progress has been made to compute a diffeomorphic harmonic map on general topology surfaces with landmark constraints. This work conquer this problem by changing the Riemannian metric on the target surface to a hyperbolic metric, so that the harmonic mapping is guaranteed to be a diffeomorphism under landmark constraints. The computational algorithms are based on the Ricci flow method and the method is general and robust. We apply our algorithm to study constrained human brain surface registration problem. Experimental results demonstrate that, by changing the Riemannian metric, the registrations are always diffeomorphic, and achieve relative high performance when evaluated with some popular cortical surface registration evaluation standards.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Pages2531-2538
Number of pages8
DOIs
StatePublished - 2013
Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013 - Portland, OR, United States
Duration: Jun 23 2013Jun 28 2013

Other

Other26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013
CountryUnited States
CityPortland, OR
Period6/23/136/28/13

Fingerprint

Brain
Computational geometry
Medical imaging
Computer graphics
Biometrics
Computer vision
Topology

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Shi, R., Zeng, W., Su, Z., Damasio, H., Lu, Z., Wang, Y., ... Gu, X. (2013). Hyperbolic harmonic mapping for constrained brain surface registration. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2531-2538). [6619171] https://doi.org/10.1109/CVPR.2013.327

Hyperbolic harmonic mapping for constrained brain surface registration. / Shi, Rui; Zeng, Wei; Su, Zhengyu; Damasio, Hanna; Lu, Zhonglin; Wang, Yalin; Yau, Shing Tung; Gu, Xianfeng.

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013. p. 2531-2538 6619171.

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

Shi, R, Zeng, W, Su, Z, Damasio, H, Lu, Z, Wang, Y, Yau, ST & Gu, X 2013, Hyperbolic harmonic mapping for constrained brain surface registration. in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition., 6619171, pp. 2531-2538, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013, Portland, OR, United States, 6/23/13. https://doi.org/10.1109/CVPR.2013.327
Shi R, Zeng W, Su Z, Damasio H, Lu Z, Wang Y et al. Hyperbolic harmonic mapping for constrained brain surface registration. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013. p. 2531-2538. 6619171 https://doi.org/10.1109/CVPR.2013.327
Shi, Rui ; Zeng, Wei ; Su, Zhengyu ; Damasio, Hanna ; Lu, Zhonglin ; Wang, Yalin ; Yau, Shing Tung ; Gu, Xianfeng. / Hyperbolic harmonic mapping for constrained brain surface registration. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013. pp. 2531-2538
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