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

Authors:
Ammar Mechouche;Christine Golbreich;Bernard Gibaud
Affiliations:
INSERM, Rennes, France and INRIA, VisAGeS, Univ. Rennes I, CNRS, UMR, Rennes, France;University of Versailles Saint-Quentin, Versailles, France;INSERM, Rennes, France and INRIA, VisAGeS, Univ. Rennes I, CNRS, UMR, Rennes, France
Venue:
RR'07 Proceedings of the 1st international conference on Web reasoning and rule systems
Year:
2007

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Abstract

This paper describes an hybrid method combining symbolic and numerical techniques for annotating brain Magnetic Resonance images. Existing automatic labelling methods are mostly statistical in nature 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 sufficient 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.