Architecture de fusion de données basée sur la théorie de l’évidence pour la reconstruction d’une vertèbre

Architecture de fusion de données basée sur la théorie de l’évidence pour la reconstruction d’une vertèbre

Structure of data fusion based on the theory of evidence for the reconstruction of vertebra

Abdelmalik Taleb-Ahmed Laurent Gautier  Michèle Rombaut 

Laboratoire d’Analyse des Systèmes du Littoral UPRES 2600 Université du Littoral Côte d’Opale

Laboratoire des Images et des Signaux UMR CNRS 5083 IUT 1 Université Joseph Fourier

Corresponding Author Email:
9 November 2001
31 December 2002
| Citation



The work presented in this article is carried out in collaboration with the department of radiology of the «Institut Calot de Berck-sur-Mer » and Siemens. This article relates to the description of an architecture of data fusion for detection of the cortical osseous one of a vertebra from magnetic resonance imaging (MRI). The goal is to determine the effective membership of points of contour obtained by active contour method to the cortical. Several parameters associated to the points are taken into account (gray level, mean of gray leveland standard deviation on a neighbourhood, outdistances between points belonging to close slices). The architecture is based on the formalism of the evidence. We discuss the results obtained, the validity of them and we propose further objectives of this work.


Cet article concerne la description d’une architecture de fusion de données pour la détection du cortical osseux d’une vertèbre dans une image IRM, développée dans le cadre d’une collaboration avec le département de radiologie de l’Institut Calot de Berck-sur-Mer et Siemens. Il s’agit de déterminer l’appartenance effective de points de contour obtenus par une méthode de segmentation par contour actif au cortical. Plusieurs paramètres associés à chacun de ces points sont pris en compte (niveau de gris, niveau de gris moyen et écart type sur un voisinage, distance entre points appartenant à des coupes voisines). L’architecture est basée sur le formalisme de la théorie de l’évidence. Nous discutons des résultats obtenus, de leur validité et nous donnons les perspectives envisagées de la suite de ce travail.


Data fusion, evidence theory (Dempster-Shafer), MRI images, 2D segmentation, snake

Mots clés

Fusion de données, théorie de l’évidence (Dempster-Shafer), images IRM, segmentation 2D, contour actif

1. Introduction
2. Présentation De La Théorie De L’évidence
3. Les Données Du Problème
4. Modélisation De La Connaissance : Les Distributions De Masse
5. L’architecture De Fusion
6. Les Résultats
7. Évaluation De La Décision
8. Conclusion Et Perspectives

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