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Ontology-Based Annotation of Brain MRI Images

Ammar Mechouche 1, * Christine Golbreich 2, 3 Xavier Morandi 1 Bernard Gibaud 1 
* Corresponding author
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.
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Submitted on : Monday, November 17, 2008 - 7:00:02 AM
Last modification on : Thursday, January 20, 2022 - 4:18:46 PM


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  • HAL Id : inserm-00331816, version 1


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. ⟨inserm-00331816⟩



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