A Motion-Aided Ultrasound Image Sequence Segmentation

D. Casaburi (), L. D’Amore (), L. Marcellino () and A. Murli ()
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D. Casaburi: University of Naples Federico II, Complesso Universitario M.S. Angelo
L. D’Amore: University of Naples Federico II, Complesso Universitario M.S. Angelo
L. Marcellino: University of Naples Parthenope, Centro Direzionale
A. Murli: University of Naples Federico II, Complesso Universitario M.S. Angelo

A chapter in Numerical Mathematics and Advanced Applications 2009, 2010, pp 217-225 from Springer

Abstract: Abstract We focus on segmentation and tracking of left ventricle and atrium (LVA) deformations in ultrasound images. We propose a fast, reliable and automatic approach to extract the LVA contour during the cardiac cycle. The approach combines a preliminary speckle reduction -based on non linear coherent diffusion model- with a motion-aided LVA border segmentation- based on geodesic level set active contours. A markers-controlled evolution of the segmentation level set surface is employed as a prior knowledge about the shape of the LVA chamber. The extent of this result is the deployment of an automatic stopping criterion. Computational kernels are sparse linear systems solved using GMRES iterative method equipped with AMG multigrid preconditioner. Experiments on real data are discussed.

Keywords: Active Contour; Motion Trajectory; Subjective Contour; Initial Contour; Segmentation Model (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-11795-4_22

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DOI: 10.1007/978-3-642-11795-4_22

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