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Model Based Spatial and Temporal Similarity Measures between Series of Functional Magnetic Resonance Images

  • Ferath Kherif
  • Guillaume Flandin
  • Philippe Ciuciu
  • Habib Benali
  • Olivier Simon
  • Jean-Baptiste Poline
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2489)

Abstract

We present a method that provides relevant distances or similarity measures between temporal series of brain functional images. The method allows to perform a multivariate comparison between data sets of several subjects in the time or in the space domain. These analyses are important to assess globally the inter subject variability before averaging subjects to draw some conclusions at the population level. We adapt the RV-coefficient to measure meaningful spatial or temporal similarities and use multidimensional scaling for visualisation.

Keywords

Canonical Correlation Analysis fMRI Data Space Domain Functional Magnetic Resonance Image fMRI Analysis 
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 2002

Authors and Affiliations

  • Ferath Kherif
    • 1
    • 2
  • Guillaume Flandin
    • 1
    • 3
  • Philippe Ciuciu
    • 1
    • 2
  • Habib Benali
    • 2
    • 4
  • Olivier Simon
    • 2
    • 5
  • Jean-Baptiste Poline
    • 1
    • 2
  1. 1.Service Hospitalier Frédéric Joliot, CEAOrsayFrance
  2. 2.Institut Fédératif de RechercheParisFrance
  3. 3.INRIA Epidaure ProjectSophia AntipolisFrance
  4. 4.INSERM UParisFrance
  5. 5.INSERM UOrsayFrance

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