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.
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CITATION STYLE
Herlin, I. L., Bereziat, D., Giraudon, G., Nguyen, C., & Graffigne, C. (1994). Segmentation of echocardiographic images with Markov random fields. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 801 LNCS, pp. 201–206). Springer Verlag. https://doi.org/10.1007/bfb0028352
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