Analyse de forme pour la segmentation de structures cérébrales 3D par ensembles de niveau et commande floue

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 a shape model and fuzzy control. To this end, several contours evolve simultaneously toward previously dened anatomical targets. A fuzzy decision system combines the a priori knowledge provided by a shape model, which is used as 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. The shape model is produced with a principal component analysis, and the resulting mean shape and variations are used to estimate the target location and the fuzzy states corresponding to the distance between the current contour and the target. The method is applied to the segmentation of the brain grey nuclei, and quantitatively assessed on a dataset of 18 volumes.
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Cybèle Ciofolo, Christian Barillot. Analyse de forme pour la segmentation de structures cérébrales 3D par ensembles de niveau et commande floue. RFIA'2006, 15ème Congrès Francophone AFRIF/AFIA de Reconnaissance des Formes et Intelligence Artificielle, 2006, France. ⟨inserm-00109468⟩

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