A surface-volume matching process using a markov random field model for cardiac motion extraction in MSCT imaging

Authors:
Antoine Simon;Mireille Garreau;Dominique Boulmier;Jean-Louis Coatrieux;Hervé Le Breton
Affiliations:
Laboratoire Traitement du Signal et de l’Image, INSERM U642, Université de Rennes 1, Rennes, France;Laboratoire Traitement du Signal et de l’Image, INSERM U642, Université de Rennes 1, Rennes, France;Centre Cardio-Pneumologique, CHU Pontchaillou, Rennes, France;Laboratoire Traitement du Signal et de l’Image, INSERM U642, Université de Rennes 1, Rennes, France;Laboratoire Traitement du Signal et de l’Image, INSERM U642, Université de Rennes 1, Rennes, France
Venue:
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
Year:
2005

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Abstract

Multislice Computed Tomography (MSCT) scanners offers new perspectives for cardiac kinetics evaluation with 3D time image sequences of high contrast and spatio-temporal resolutions. A new method is proposed for cardiac motion extraction in Multislice CT. Based on a 3D surface-volume matching process, it provides the detection of the heart left cavities along the acquired sequence and the estimation of their 3D surface velocity fields. A 3D segmentation step and surface reconstruction process are first applied on only one image of the sequence to obtain a 3D mesh representation for one t time. A Markov Random Field model is defined to find best correspondences between 3D mesh nodes at t time and voxels in the next volume at t + 1 time. A simulated annealing is used to perform a global optimization of the correspondences. First results obtained on simulated and real data show the good behaviour of this method.