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Multivariate Statistical Analysis of Deformation Momenta Relating Anatomical Shape to Neuropsychological Measures

  • Nikhil Singh
  • P. Thomas Fletcher
  • J. Samuel Preston
  • Linh Ha
  • Richard King
  • J. Stephen Marron
  • Michael Wiener
  • Sarang Joshi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6363)

Abstract

The purpose of this study is to characterize the neuroanatomical variations observed in neurological disorders such as dementia. We do a global statistical analysis of brain anatomy and identify the relevant shape deformation patterns that explain corresponding variations in clinical neuropsychological measures. The motivation is to model the inherent relation between anatomical shape and clinical measures and evaluate its statistical significance. We use Partial Least Squares for the multivariate statistical analysis of the deformation momenta under the Large Deformation Diffeomorphic framework. The statistical methodology extracts pertinent directions in the momenta space and the clinical response space in terms of latent variables. We report the results of this analysis on 313 subjects from the Mild Cognitive Impairment group in the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Keywords

Mild Cognitive Impairment Partial Little Square Multivariate Statistical Analysis Partial Little Square Analysis Mild Cognitive Impairment Group 
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 2010

Authors and Affiliations

  • Nikhil Singh
    • 1
  • P. Thomas Fletcher
    • 1
  • J. Samuel Preston
    • 1
  • Linh Ha
    • 1
  • Richard King
    • 1
  • J. Stephen Marron
    • 2
  • Michael Wiener
    • 3
  • Sarang Joshi
    • 1
  1. 1.University of UtahSalt Lake City
  2. 2.University of North Carolina at Chapel HillChapel Hill
  3. 3.University of CaliforniaSan Francisco

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