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Automatic quantification of multiple sclerosis lesion volume using stereotaxic space

  • Alex Zijdenbos
  • Alan Evans
  • Farhad Riahi
  • John Sled
  • Joe Chui
  • Vasken Kollokian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1131)

Abstract

The quantitative analysis of MRI data is becoming increasingly important in the evaluation of therapies for the treatment of MS. This paper describes a processing environment for the automatic quantification of lesion load from large ensembles of MR volume data. The main components of this approach are stereotaxic transformation and multispectral classification, supported by pre- and postprocessing techniques to reduce noise and correct for intensity non-uniformities. The results of the automated approach are compared with those obtained by manual lesion delineation, showing a significant lesion volume correlation of 0.94.

Key words

MRI multiple sclerosis tissue quantification image segmentation stereotaxic space 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Alex Zijdenbos
    • 1
  • Alan Evans
    • 1
  • Farhad Riahi
    • 1
  • John Sled
    • 1
  • Joe Chui
    • 1
  • Vasken Kollokian
    • 1
  1. 1.McConnell Brain Imaging Centre, Montréal Neurological InstituteMcGill UniversityMontréalCanada

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