Authors:
Emna Amdouni
and
Bernard Gibaud
Affiliation:
E-health department, B-com Institute of Research and Technology, Rennes, France, LTSI Inserm 1099, Université de Rennes 1, Rennes and France
Keyword(s):
Medical Domain Ontology, Knowledge Representation, Ontology Reuse and Alignment.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
e-Business
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontology Matching and Alignment
;
Ontology Sharing and Reuse
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
The main objective of this work is to facilitate the identification, sharing and reasoning about cerebral tumors observations via the formalization of their semantic meanings in order to facilitate their exploitation in both the clinical practice and research. We have focused our analysis on the VASARI terminology as a proof of concept, but we are convinced that our work can be useful in other biomedical imaging contexts. In this paper, we propose (1) a methodology, a domain ontology and an annotation tool for providing unambiguous formal definitions of neuroimaging data, (2) an experimental work on the REMBRANDT dataset to demonstrate the added value of our work over existing methods, namely DICOM SR and the AIM model.