Genus zero surface conformal mapping and its application to brain surface mapping

Xianfeng Gu, Yalin Wang, Tony F. Chan, Paul M. Thompson, Shing Tung Yau

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

It is well known that any genus zero surface can be mapped conformally onto the sphere and any local portion thereof onto a disk. However, it is not trivial to find a general method which finds a conformal mapping between two general genus zero surfaces. We propose a new variational method which can find a unique mapping between any two genus zero manifolds by minimizing the harmonic energy of the map. We demonstrate the feasibility of our algorithm by applying it to the cortical surface matching problem. We use a mesh structure to represent the brain surface. Further constraints are added to ensure that the conformal map is unique. Empirical tests on MRI data show that the mappings preserve angular relationships, are stable in MRIs acquired at different times, and are robust to differences in data triangulation, and resolution. Compared with other brain surface conformal mapping algorithms, our algorithm is more stable and has good extensibility.

Original languageEnglish (US)
Pages (from-to)172-184
Number of pages13
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2732
StatePublished - 2003
Externally publishedYes

Fingerprint

Brain Mapping
Conformal mapping
Conformal Mapping
Brain
Genus
Zero
Magnetic resonance imaging
Conformal Map
Triangulation
Matching Problem
Variational Methods
Trivial
Harmonic
Mesh
Energy
Demonstrate

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Genus zero surface conformal mapping and its application to brain surface mapping. / Gu, Xianfeng; Wang, Yalin; Chan, Tony F.; Thompson, Paul M.; Yau, Shing Tung.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2732, 2003, p. 172-184.

Research output: Contribution to journalArticle

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