Automatic contour extraction in images using a 2-D hidden Markov model

Abstract : A new entirely automatic method is proposed to detect the contour of an object in low contrast medical images. The contour extraction is based on a tight cooperation between a multiresolution neural network and a hidden Markov model-enhanced dynamic procedure. Such a modelization allows to introduce relevant high order a priori information at different stages of the extraction process. An application to the automatic detection of the left ventricle in digital X-ray images is proposed.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01574992
Contributor : Lip6 Publications <>
Submitted on : Thursday, August 17, 2017 - 11:25:44 AM
Last modification on : Thursday, March 21, 2019 - 1:06:23 PM

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Olivier Gérard, Florence d'Alché-Buc, Sherif Makram-Ebeid, Patrick Gallinari, Thierry Artières. Automatic contour extraction in images using a 2-D hidden Markov model. ICANN'99 - 9th International Conference on Artificial Neural Networks, Sep 1999, Edinburgh, United Kingdom. pp.455-460, ⟨10.1049/cp:19991151⟩. ⟨hal-01574992⟩

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