Towards an hybrid system using an ontology enriched by rules for the semantic annotation of brain MRI images.

Ammar Mechouche 1 Christine Golbreich 2 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 an hybrid method combining symbolic and numerical techniques for annotating brain Magnetic Resonance im- ages. Existing automatic labelling methods are mostly statistical in na- ture and do not work very well in certain situations such as the presence of lesions. The goal is to assist them by a knowledge-based method. The system uses statistical method for generating a sucient set of initial facts for fruitful reasoning. Then, the reasoning is supported by an OWL DL ontology enriched by SWRL rules. The experiments described were achieved using the KAON2 reasoner for inferring the annotations.
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Submitted on : Monday, June 4, 2007 - 3:53:05 PM
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Ammar Mechouche, Christine Golbreich, Bernard Gibaud. Towards an hybrid system using an ontology enriched by rules for the semantic annotation of brain MRI images.. The First International Conference on Web Reasoning and Rule Systems (RR2007), Jun 2007, Innsbruck, Australia. ⟨inserm-00151043⟩

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