Abstract
The aim of this work is to track specific anatomical structures in temporal sequences of echocardiographic images. This paper presents a new spatio-temporal model and describes the relevant spatial and temporal properties that must be taken into consideration to obtain the best possible results. It is expressed within a Markov random field framework and results are presented with different formulations of the temporal properties.
Chapter PDF
References
R. Azencott and C. Graffigne. Non supervised segmentation using multi-level markov random fields. In Proceedings of the 11th International Conference on Pattern Recognition, August 30–September 3 1992.
R. Deriche. Using Canny's criteria to derive a recursively implemented optimal edge detector. International Journal of Computer Vision, 1 (2), May 1987.
S. Geman and D. Geman. Stochastic relaxation, Gibbs distribution and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6:712–741, 1984.
I. L. Herlin and G. Giraudon. Use of temporal information in a segmentation algorithm of ultrasound images. In Proceedings of the conference on Computer Vision and Pattern Recognition, New York, U.S.A., 15–17 June 1993.
I. Herlin, C. Nguyen, and C. Graffigne. Stochastic segmentation of ultrasound images. In Proceedings of the 11th International Conference on Pattern Recognition, August 30–September 3 1992.
S.W. Zucker. Region growing: Childhood and adolescence. Computer Graphics and Image Processing, (5):382–399, 1976.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1994 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Herlin, I.L., Bereziat, D., Giraudon, G., Nguyen, C., Graffigne, C. (1994). Segmentation of echocardiographic images with Markov random fields. In: Eklundh, JO. (eds) Computer Vision — ECCV '94. ECCV 1994. Lecture Notes in Computer Science, vol 801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028352
Download citation
DOI: https://doi.org/10.1007/BFb0028352
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-57957-1
Online ISBN: 978-3-540-48400-4
eBook Packages: Springer Book Archive