Résumé
This paper describes a hybrid system for annotating anatomical structures in brain Magnetic Resonance Images. The system involves both numerical knowledge from an atlas and symbolic knowledge represented in a rule-extended ontology, written in standard web languages, and symbolic constraints. The system combines this knowledge with graphical data automatically extracted from the images. The annotations of the parts of sulci and of gyri located in a region of interest selected by the user are obtained with a reasoning based on a Constraint Satisfaction Problem solving combined with Description Logics inference services. The first results obtained with both normal and pathological data are promising.