Open AccessCurve matching on brain surfaces using frenet distances
Author(s) -
Bakırcioğlu M.,
Grenander U.,
Khaneja and N.,
Miller M.I.
Publication year - 1998
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/(sici)1097-0193(1998)6:5/6<329::aid-hbm1>3.0.co;2-x
Subject(s) - frenet–serret formulas , curvature , torsion of a curve , diffeomorphism , matching (statistics) , mathematics , mathematical analysis , geometry , artificial intelligence , principal curvature , computer science , mean curvature , statistics
This paper describes methods for diffeomorphic matching of curves on brain surfaces. Distances between curves are defined by Frenet representation via speed, curvature, and torsion. The curve‐matching algorithm is based on bipartite graph matching, with weights defined by the Frenet distance over diffeomorphic maps of one curve onto the other (Sedgewick [1983]: Algorithms). We follow Khaneja ([1996]: Statistics and Geometry of Cortical Features) and define fundus curves on the brain surfaces as extremal curvature lines generated using dynamic programming. Examples are shown for fundus curve matchings on macaque brain surfaces. Hum. Brain Mapping 6:329–333, 1998. © 1998 Wiley‐Liss, Inc.