Segmentation of echocardiographic images with Markov random fields

Abstract : The aim of this work is to track specific anatomical structures in temporal sequences of echocardiographic images. Ultrasound images are available in two broad data types: raw or video data. Different stochastic processes using different kind of information are compared on the basis of these two data types. We explain the selection of a particular model w.r.t. the type of data, and describe the relevant properties that must be taken into account to obtain the best possible results. The models are expressed within a Markov random field framework and we also discuss parameter estimation and energy minimization for the different models.
Type de document :
[Research Report] RR-2424, INRIA. 1994
Liste complète des métadonnées
Contributeur : Rapport de Recherche Inria <>
Soumis le : mercredi 24 mai 2006 - 14:51:44
Dernière modification le : samedi 27 janvier 2018 - 01:30:56
Document(s) archivé(s) le : lundi 5 avril 2010 - 00:07:16



  • HAL Id : inria-00074251, version 1



Isabelle Herlin, Dominique Béréziat, Gérard Giraudon, Catherine Nguyen, Christine Graffigne. Segmentation of echocardiographic images with Markov random fields. [Research Report] RR-2424, INRIA. 1994. 〈inria-00074251〉



Consultations de la notice


Téléchargements de fichiers