Estimation combinée de forme et de mouvement par champs markoviens: application à l'imagerie cardiaque scanner multibarrette

Estimation combinée de forme et de mouvement par champs markoviens: application à l'imagerie cardiaque scanner multibarrette

Joint Shape and Motion Estimation using Markovian Fields : Application to Multislice Computed Tomography Cardiac Imaging

Antoine Simon Mireille Garreau  Dominique Boulmier   Jean-Jacques Bellanger  Hervé Le Breton 

INSERM U642, LTSI Campus de Beaulieu, Bât. 22, 35042 Rennes Cedex, France, Laboratoire Traitement du Signal et de l'Image, Université de Rennes 1, Campus de Beaulieu, Bât. 22, 35042 Rennes Cedex, France

Centre Cardio-Pneumologique, CHU Pontchaillou, 35033 Rennes, France

Corresponding Author Email: 
antoine.simon@univ-rennes1.fr
Page: 
473-487
|
Received: 
N/A
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Accepted: 
N/A
|
Published: 
31 December 2006
| Citation

OPEN ACCESS

Abstract: 

We propose a method for joint surface and non-rigid motion estimation from three-dimensional dynamic sequences. Based on a surface-volume matching, it provides, from one first segmented surface, both motion and deformations of the object of interest along the whole sequence. A Markovian model, combined with a simulated annealing process, estimates the correspondences between the nodes of the surface mesh modeling the object of interest at one time and the voxels of the volume representing the object at the following time. The method has been applied to cardiac surface and motion extraction in Multislice Computed Tomography. Tests realized with simulated motion and on real data have provided promising results.

Résumé

Une méthode d'estimation conjointe de forme et de mouvement non rigide à partir de séquences temporelles tridimensionnelles est proposée. Reposant sur une mise en correspondance surface-volume, elle permet, à partir d'une première segmentation de l'objet d'intérêt, d'estimer le mouvement de l'objet et ses déformations sur toute la séquence temporelle d'observation. Une modélisation markovienne combinée à un algorithme de recuit simulé estime les correspondances entre les nœuds du maillage de surface modélisant l'objet à un instant et les voxels du volume représentant l'objet à l'instant suivant. La méthode a été appliquée à l'extraction de formes et de mouvements cardiaques en tomodensitométrie multibarrette. Les tests, réalisés à la fois avec des mouvements simulés et sur des données réelles, ont donné des résultats prometteurs.

Keywords: 

Motion estimation, 3D dynamic CT imaging, cardiac motion, Markov random field

Mots clés

Estimation de mouvement, imagerie scanner tridimensionnelle dynamique, mouvement cardiaque, champ de Markov

1. Introduction
2. État De L’art
3. Méthode
4. Résultats
5. Conclusion Et Perspectives
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