Automatic analysis of normal brain dissymmetry of males and females in MR images

  • Sylvain Prima
  • Jean-Philippe Thirion
  • Gérard Subsol
  • Neil Roberts
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1496)


In this paper, we present a statistical analysis of the normal dissymmetry in brain MR images. Our method consists in: computing a dense 3D field characterizing the dissymmetry of a subject, analysing it with an operator (relative volume variation), computing 3D statistical maps from populations of subjects (learning series) and extracting interesting regions. The results are then tested on an independent validation series. We use a database of 36 normal young subjects, 18 males and 18 females, strongly right-handed. We show that the brain hemispheres can be reliably discriminated thanks to a consistent size difference in the white matter of the temporal and frontal lobes, with a very high level of confidence (36/36, α-value=0.000001). We also exhibit a difference of brain dissymmetry with respect to sex.


Left Hemisphere Learning Series Reference Subject Validation Series Dissymmetry Field 
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 1998

Authors and Affiliations

  • Sylvain Prima
    • 1
  • Jean-Philippe Thirion
    • 2
  • Gérard Subsol
    • 1
  • Neil Roberts
    • 3
  1. 1.EPIDAURE ProjectINRIA Sophia AntipolisFrance
  2. 2.Focus Imaging SASophia AntipolisFrance
  3. 3.MARIARCUniversity of LiverpoolUK

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