Piecewise Geodesics for Vessel Centerline Extraction and Boundary Delineation with Application to Retina Segmentation
Chen, Da; Cohen, Laurent D. (2015), Piecewise Geodesics for Vessel Centerline Extraction and Boundary Delineation with Application to Retina Segmentation, in Jean-François Aujol, Mila Nikolova, Nicolas Papadakis, Scale Space and Variational Methods in Computer Vision 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings, Springer : Berlin Heidelberg, p. 270-281. 10.1007/978-3-319-18461-6_22
TypeCommunication / Conférence
External document linkhttps://hal.archives-ouvertes.fr/hal-01250017
Book titleScale Space and Variational Methods in Computer Vision 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings; SSVM'15
Book authorJean-François Aujol, Mila Nikolova, Nicolas Papadakis
MetadataShow full item record
Abstract (EN)Geodesic methods have been widely applied to image analysis . In this paper, we propose an automatic anisotropic fast marching based geodesic method to extract the centrelines of retinal vessel segments and their boundaries. Our method is related to the geodesic or minimal path technique which is particularly efficient to extract a tubular shape, such as a blood vessel. The proposed method consists of a set of pairs of points. Each pair of points provides the Initial point and Target point for one geodesic. For each pair of Initial point and Target point, we calculate a special Riemannian metric with an additional Radius dimension to constrain the fast marching propagation so that our method can get a nice path without any shortcut. The given pairs of points can be easily obtained from a pre-segmented skeletonized image by any vessel detection filter like Hessian or Oriented Flux method. Experimental results demonstrate that our method can extract vessel segments at a finer scale, with increased accuracy.
Subjects / KeywordsGeodesic; Minimal path; Tubular structure extraction; Retinal vessel segmentation; Anisotropic fast marching
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