3D brain surface matching based on geodesics and local geometry

Authors:
Yongmei Wang;Bradley S. Peterson;Lawrence H. Staib
Affiliations:
Departments of Diagnostic Radiology and Electrical Engineering, Yale University School of Medicine, P.O. Box 208042, 333 Cedar Street, New Haven, CT;Department of Psychiatry, Columbia University, New York, NY;Departments of Diagnostic Radiology and Electrical Engineering, Yale University School of Medicine, P.O. Box 208042, 333 Cedar Street, New Haven, CT
Venue:
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Year:
2003

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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.