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Incorporating Statistical Measures of Anatomical Variability in Atlas-to-Subject Registration for Conformal Brain Radiotherapy

  • Olivier Commowick
  • Radu Stefanescu
  • Pierre Fillard
  • Vincent Arsigny
  • Nicholas Ayache
  • Xavier Pennec
  • Grégoire Malandain
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3750)

Abstract

Deforming a digital atlas towards a patient image allows the simultaneous segmentation of several structures. Such an intersubject registration is difficult as the deformations to recover are highly inhomogeneous. A priori information about the local amount of deformation to expect is precious, since it allows to optimally balance the quality of the matching versus the regularity of the deformation. However, intersubject variability makes it hard to heuristically estimate the degree of deformation. Indeed, the sizes and shapes of various structures differ greatly and their relative positions vary in a rather complex manner. In this article, we perform a statistical study of the deformations yielded by the registration of an image database with an anatomical atlas, and we propose methods to re-inject this information into the registration. We show that this provides more accurate segmentations of brain structures.

Keywords

Fractional Anisotropy Patient Image Anatomical Variability Anatomical Atlas Atlas Image 
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 2005

Authors and Affiliations

  • Olivier Commowick
    • 1
    • 2
  • Radu Stefanescu
    • 1
  • Pierre Fillard
    • 1
  • Vincent Arsigny
    • 1
  • Nicholas Ayache
    • 1
  • Xavier Pennec
    • 1
  • Grégoire Malandain
    • 1
  1. 1.Epidaure ProjectINRIA SophiaSophia Antipolis CedexFrance
  2. 2.DOSISoft S.A.CachanFrance

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