Incorporating statistical measures of anatomical variability in atlas-to-subject registration for conformal brain radiotherapy.

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.
Type de document :
Communication dans un congrès
J. Duncan and G. Gerig. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005, Oct 2005, Palm Springs, CA, United States. Springer-Verlag, 3750 (Pt 2), pp.927-34, 2005, Lecture Notes in Computer Science - LNCS. 〈10.1007/11566489_114〉
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https://hal.inria.fr/inria-00502673
Contributeur : Pierre Fillard <>
Soumis le : jeudi 15 juillet 2010 - 14:32:30
Dernière modification le : samedi 2 décembre 2017 - 01:26:02

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Olivier Commowick, Radu Stefanescu, Pierre Fillard, Vincent Arsigny, Nicholas Ayache, et al.. Incorporating statistical measures of anatomical variability in atlas-to-subject registration for conformal brain radiotherapy.. J. Duncan and G. Gerig. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005, Oct 2005, Palm Springs, CA, United States. Springer-Verlag, 3750 (Pt 2), pp.927-34, 2005, Lecture Notes in Computer Science - LNCS. 〈10.1007/11566489_114〉. 〈inria-00502673〉

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