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MRI image artifact ontology: a proposed method for improved recognition.
Lasbleiz, Jeremy; Morelli, John; Schnel, Nicolas; Burgun, Anita; Duvauferrier, Régis; Saint Jalmes, Hervé.
Afiliación
  • Lasbleiz J; Faculté de Médecine, University of Rennes, France. jeremy.lasbleiz@chu-rennes.fr
Stud Health Technol Inform ; 180: 103-7, 2012.
Article en En | MEDLINE | ID: mdl-22874161
ABSTRACT
UNLABELLED 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.
Asunto(s)
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Bases de datos: MEDLINE Asunto principal: Algoritmos / Interfaz Usuario-Computador / Programas Informáticos / Reconocimiento de Normas Patrones Automatizadas / Aumento de la Imagen / Sistemas de Información Radiológica / Artefactos / Minería de Datos Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2012 Tipo del documento: Article País de afiliación: Francia
Buscar en Google
Bases de datos: MEDLINE Asunto principal: Algoritmos / Interfaz Usuario-Computador / Programas Informáticos / Reconocimiento de Normas Patrones Automatizadas / Aumento de la Imagen / Sistemas de Información Radiológica / Artefactos / Minería de Datos Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2012 Tipo del documento: Article País de afiliación: Francia