Ontology-Based Annotation of Brain MRI Images

Ammar Mechouche 1, * Christine Golbreich 2, 3 Xavier Morandi 1 Bernard Gibaud 1
* Auteur correspondant
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 : 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.
Type de document :
Communication dans un congrès
AMIA - American Medical Informatics Association, Nov 2008, Washington, United States. 2008
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Soumis le : lundi 17 novembre 2008 - 07:00:02
Dernière modification le : jeudi 15 novembre 2018 - 11:57:30

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  • HAL Id : inserm-00331816, version 1

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Ammar Mechouche, Christine Golbreich, Xavier Morandi, Bernard Gibaud. Ontology-Based Annotation of Brain MRI Images. AMIA - American Medical Informatics Association, Nov 2008, Washington, United States. 2008. 〈inserm-00331816〉

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