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Brain segmentation with competitive level sets and fuzzy control.

Cybèle Ciofolo 1 Christian Barillot 1 
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : We propose to segment 3D structures with competitive level sets driven by fuzzy control. To this end, several contours evolve simultaneously toward previously defined anatomical targets. A fuzzy decision system combines the a priori knowledge provided by an anatomical atlas with the intensity distribution of the image and the relative position of the contours. This combination automatically determines the directional term of the evolution equation of each level set. This leads to a local expansion or contraction of the contours, in order to match the borders of their respective targets. Two applications are presented: the segmentation of the brain hemispheres and the cerebellum, and the segmentation of deep internal structures. Experimental results on real MR images are presented, quantitatively assessed and discussed.
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Submitted on : Tuesday, March 20, 2007 - 12:01:50 PM
Last modification on : Thursday, January 20, 2022 - 4:20:26 PM


  • HAL Id : inserm-00137473, version 1
  • PUBMED : 17354707


Cybèle Ciofolo, Christian Barillot. Brain segmentation with competitive level sets and fuzzy control.. Information processing in medical imaging : proceedings of the .. conference., Springer-Verlag, 2005, 19, pp.333-44. ⟨inserm-00137473⟩



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