A Deformable Region Model using Stochastic Processes applied to Echocardiographic Images

Isabelle Herlin 1, * C. Nguyen 1, * Christine Graffigne 1, *
* Auteur correspondant
Résumé : The problem of improving an initial segmentation of medical data by making use of gray level, texture, and gradient information is addressed. The mathematical environment is that of Markov random fields and stochastic processes. This yields two major advantages: automatic selection of program parameters and ergonomic software that can be used to test homogeneity properties of regions. The method is applied to echocardiographic images in order to segment cardiac cavities.
Type de document :
Communication dans un congrès
Proceedings of the conference on Computer Vision and Pattern Recognition, Jun 1992, Champaign, Illinois, U.S.A., United States. 1992, 〈10.1109/CVPR.1992.223139〉
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https://hal.inria.fr/inria-00615577
Contributeur : Project-Team Asclepios <>
Soumis le : vendredi 19 août 2011 - 16:49:46
Dernière modification le : samedi 23 avril 2016 - 01:04:04

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Isabelle Herlin, C. Nguyen, Christine Graffigne. A Deformable Region Model using Stochastic Processes applied to Echocardiographic Images. Proceedings of the conference on Computer Vision and Pattern Recognition, Jun 1992, Champaign, Illinois, U.S.A., United States. 1992, 〈10.1109/CVPR.1992.223139〉. 〈inria-00615577〉

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