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3D Moment Invariant Based Morphometry

  • J. -F. Mangin
  • F. Poupon
  • D. Rivière
  • A. Cachia
  • D. L. Collins
  • A. C. Evans
  • J. Régis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2879)

Abstract

This paper advocates the use of shape descriptors based on moments of 3D coordinates for morphometry of the cortical sulci. These descriptors, which have been introduced more than a decade ago, are invariant relatively to rotations, symmetry and scale and can be computed for any topology. A rapid insight of the derivation of these invariants is proposed first. Then, their potential to characterize shapes is shown from a principal component analysis of the 12 first invariants computed for 12 different deep brain structures manually drawn from 7 different brains. Finally, these invariants are used to find some correlates of handedness among the shapes of 116 different cortical sulci automatically identified in 144 brains of the ICBM database.

Keywords

Central Moment Shape Space Asymmetry Index Moment Invariant Central Sulcus 
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 2003

Authors and Affiliations

  • J. -F. Mangin
    • 1
    • 2
  • F. Poupon
    • 1
    • 2
  • D. Rivière
    • 1
    • 2
  • A. Cachia
    • 1
    • 2
  • D. L. Collins
    • 3
  • A. C. Evans
    • 3
  • J. Régis
    • 4
  1. 1.Service Hospitalier Frédéric JoliotCEAOrsayFrance
  2. 2.Institut Fédératif de Recherche 49 (Imagerie NeurofonctionnelleParis
  3. 3.Montreal Neurological InstituteMcGill UniversityMontreal
  4. 4.Service de Neurochirurgie Fonctionnelle et Stereotaxique, CHU La TimoneMarseille

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