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Vessel Tree Segmentation Via Front Propagation and Dynamic Anisotropic Riemannian Metric

Chen, Da; Cohen, Laurent D. (2016), Vessel Tree Segmentation Via Front Propagation and Dynamic Anisotropic Riemannian Metric, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), IEEE : Piscataway, NJ. 10.1109/ISBI.2016.7493465

Type
Communication / Conférence
Date
2016
Conference country
CZECH REPUBLIC
Book title
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI); ISBI 2016
Publisher
IEEE
Published in
Piscataway, NJ
ISBN
978-1-4799-2349-6
Publication identifier
10.1109/ISBI.2016.7493465
Metadata
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Author(s)
Chen, Da

Cohen, Laurent D.
Abstract (EN)
In this paper, we present a blood vessel segmentation method by front propagation and anisotropic Riemannian metric. The front is defined as the level set of the geodesic distance to a set of given initial source points, with respect to a dynamic anisotropic Riemannian metric. The boundaries of the vessels can be represented by the level set at the given distance threshold. The anisotropic Riemannian metric can be defined using a prior estimate of the vessel orientations and the local intensity difference values, where the vessel orientations are detected by the oriented flux filter. Experimental results demonstrate the proposed vessel detection method indeed outperforms the traditional vesselness based detection method.
Subjects / Keywords
dynamic anisotropic; Riemannian metric; Vessel tree segmentation; level set; Fast Marching method

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