3 research outputs found

    Segmentation of nerve bundles and ganglia in spine MRI using particle filters

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    14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part IIIAutomatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation.National Institutes of Health (U.S.) (NAMIC award U54-EB005149)National Science Foundation (U.S.) (CAREER grant 0642971

    Segmentation of nerve bundles and ganglia in spine MRI using particle filters

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 41-44).Automatic segmentation of spinal nerve bundles originating within the dural sac and exiting the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this thesis, we present an automatic tracking method for segmentation of nerve bundles based on particle filters. We develop a novel approach to flexible particle representation of tubular structures based on Bezier splines. We construct an appropriate dynamics to reflect the continuity and smoothness properties of real nerve bundles. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We evaluate the results by comparing them to expert manual segmentation, and we demonstrate accurate and fast nerve tracking.by Adrian Vasile Dalca.S.M
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