Using Local Geometry to Build 3D Sulcal Models

  • A. Caunce
  • C. J. Taylor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1613)

Abstract

This paper presents a series of 3D statistical models of the cortical sulci. They are built from points located automatically over the sulcal fissures, and corresponded automatically using variants on the Iterative Closest Point algorithm. The models are progressively improved by adding in more and more structural and configural information, and the final results are consistent with findings from other anatomical studies. The models can be used to locate and label anatomical features automatically in 3D head images for analysis, visualisation, classification, and normalisation.

Keywords

Iterative Close Point Local Geometry Curve Segment Point Correspondence Iterative Close Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • A. Caunce
    • 1
  • C. J. Taylor
    • 1
  1. 1.Wolfson Image Analysis Unit, Department of Medical BiophysicsUniversity of ManchesterManchesterUK

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