3D brain surface matching based on geodesics and local geometry

Yongmei Wang, Bradley S. Peterson, Lawrence H. Staib

Research output: Contribution to journalArticle

Abstract

The non-rigid registration of surfaces is a complex and difficult task for which there are many important applications, such as comparing shape between deformable objects and comparing associated function. This paper presents a new approach for brain surface matching by determining the correspondence of 3D point sets between pairs of surfaces. The algorithm is based on shape using a combination of geodesic distance and surface curvature. There are two major procedures involved. An initial sparse set of corresponding points is first generated by matching local geometrical features. Geodesic distance interpolation is then employed hierarchically in order to capture the complex surface. By this scheme, surface correspondence and triangulation are computed simultaneously. Experiments applied to human cerebral cortical surfaces are shown to evaluate the approach. It is shown that the proposed method performs well for both surface matching and surface shape recovery.

Original languageEnglish (US)
Pages (from-to)252-271
Number of pages20
JournalComputer Vision and Image Understanding
Volume89
Issue number2-3
DOIs
StatePublished - Jan 1 2003
Externally publishedYes

Keywords

  • Correspondence
  • Corresponding points
  • Geodesics
  • Geometrical features
  • Shape
  • Shortest paths
  • Surface matching
  • Triangulation

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

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