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Improved Detection Sensitivity in Functional MRI Data Using a Brain Parcelling Technique

  • Guillaume Flandin
  • Ferath Kherif
  • Xavier Pennec
  • Grégoire Malandain
  • Nicholas Ayache
  • Jean-Baptiste Poline
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2488)

Abstract

We present a comparison between a voxel based approach and a region based technique for detecting brain activation signals in sequences of functional Magnetic Resonance Images (fMRI). The region based approach uses an automatic parcellation of the brain that can incorporate anatomical constraints. A standard univariate voxel based detection method (Statistical Parametric Mapping [5] is used and the results are compared to those obtained when performing detection of signals extracted from the parcels. Results on a fMRI experimental protocol are presented and show a greater sensitivity using the parcelling technique. This result remains true when the data are analyzed at several resolutions.

Keywords

Point Spread Function Geodesic Distance Functional Magnetic Resonance Image Human Brain Mapping Anatomical Constraint 
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

  • Guillaume Flandin
    • 1
    • 2
    • 3
  • Ferath Kherif
    • 2
    • 3
  • Xavier Pennec
    • 1
  • Grégoire Malandain
    • 1
  • Nicholas Ayache
    • 1
  • Jean-Baptiste Poline
    • 2
    • 3
  1. 1.Epidaure ProjectINRIASophia AntipolisFrance
  2. 2.CEAService Hospitalier Frédéric JoliotOrsayFrance
  3. 3.Neuroimagerie fonctionnelleIFR 49ParisFrance

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