Skip to Main content Skip to Navigation
Conference papers

Ontology-Based Annotation of Brain MRI Images

Ammar Mechouche 1, * Christine Golbreich 2, 3 Xavier Morandi 1 Bernard Gibaud 1
* Corresponding author
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE, INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique
Abstract : This paper describes a hybrid system for annotating anatomical structures in brain Magnetic Resonance Images. The system involves both numerical knowledge from an atlas and symbolic knowledge represented in a rule-extended ontology, written in standard web languages, and symbolic constraints. The system combines this knowledge with graphical data automatically extracted from the images. The annotations of the parts of sulci and of gyri located in a region of interest selected by the user are obtained with a reasoning based on a Constraint Satisfaction Problem solving combined with Description Logics inference services. The first results obtained with both normal and pathological data are promising.
Complete list of metadatas

Cited literature [10 references]  Display  Hide  Download

https://www.hal.inserm.fr/inserm-00331816
Contributor : Aline Grosset <>
Submitted on : Monday, November 17, 2008 - 7:00:02 AM
Last modification on : Friday, January 10, 2020 - 3:42:22 PM

File

AMIA2008-AMCGXMBG.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inserm-00331816, version 1

Citation

Ammar Mechouche, Christine Golbreich, Xavier Morandi, Bernard Gibaud. Ontology-Based Annotation of Brain MRI Images. AMIA - American Medical Informatics Association, Nov 2008, Washington, United States. ⟨inserm-00331816⟩

Share

Metrics

Record views

1553

Files downloads

223