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An automated myocardial segmentation in cardiac MRI.

Abstract : In this paper we present an automatic approach to segment Cardiac Magnetic Resonance (CMR) images. A preprocessing step that consists in filtering the image using connected operators (area opening and closing filters) is applied in order to homogenize the cavity and solve the problems due to the papillary muscles. Thereby the GVF snake algorithm is applied with one point clicked in the cavity as initialization and an optimized tuning of parameters for the endocardial contour extraction. The epicardial border is then obtained using the endocardium as initialization. The performance of the proposed method was assessed by experimentation on thirtynine CMR images. A high agreement between manual and automatic contours was obtained with correlation scores of 0.96 for the endocardium and 0.90 for the epicardium. Overlapping percentage, mean and maximum distances between the two contours show a good performance of the method.
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Contributor : Racha El Berbari <>
Submitted on : Thursday, December 6, 2007 - 12:59:58 PM
Last modification on : Monday, December 14, 2020 - 9:46:52 AM
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Racha El Berbari, Isabelle Bloch, Alban Redheuil, Elsa Angelini, Elie Mousseaux, et al.. An automated myocardial segmentation in cardiac MRI.. Conference proceedings : .. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Institute of Electrical and Electronics Engineers (IEEE), 2007, 1, pp.4508-11. ⟨10.1109/IEMBS.2007.4353341⟩. ⟨inserm-00194347⟩



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