MRI image artifact ontology: A Proposed Method for Improved Recognition.

Jeremy Lasbleiz 1 John Morelli 1 Nicolas Schnel 2 Anita Burgun 1 Régis Duvauferrier 1 Hervé Saint-Jalmes 3
1 Modélisation Conceptuelle des Connaissances Biomédicales
2 SYMBIOSE - Biological systems and models, bioinformatics and sequences
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
3 LTSI - Laboratoire Traitement du Signal et de l'Image
Abstract : Magnetic Resonance Imaging is an essential diagnostic imaging technique. The complexity of interpreting MRI images is often compounded by the presence of a wide range of artifacts which are often challenging to identify and eliminate. Ontology permits the construction of a knowledge database with which users can interact given an appropriate interface. The goal of this work is to create an interactive tool for the ontology of MRI artifacts that will allow a radiologist to compare any given MRI artifact image with those contained in the ontology. Material and method: Using Protégé 4, we have constructed the ontology with input from an expert in MRI artifacts and utilizing images exemplifying such artifacts. The graphical user interface has been built in Java and the linkage with the ontology made with Owl API. Results: Using the tool, users can compare imaging artifacts encountered in daily practice to those in the database. Once a user has identified the image the most similar to their own, they then have instantaneous access to the knowledge contained in the ontology about the artifact. Individual users can also submit images and have access to DICOM data.
Type de document :
Article dans une revue
Studies in Health Technology and Informatics, IOS Press, 2012, 180, pp.103-7. 〈10.3233/978-1-61499-101-4-103〉
Liste complète des métadonnées
http://www.hal.inserm.fr/inserm-00748002
Contributeur : Lotfi Senhadji <>
Soumis le : samedi 3 novembre 2012 - 11:48:38
Dernière modification le : mercredi 16 mai 2018 - 11:23:40

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INRIA | IRISA | LTSI | BIOSIT | IRISA-D7 | UR1-UFR-ISTIC | UNIV-RENNES

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Jeremy Lasbleiz, John Morelli, Nicolas Schnel, Anita Burgun, Régis Duvauferrier, et al.. MRI image artifact ontology: A Proposed Method for Improved Recognition.. Studies in Health Technology and Informatics, IOS Press, 2012, 180, pp.103-7. 〈10.3233/978-1-61499-101-4-103〉. 〈inserm-00748002〉

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