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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Multi-scale Vessel Boundary Detection
verfasst von : Hüseyin Tek, Alper Ayvacı, Dorin Comaniciu
Erschienen in: Computer Vision for Biomedical Image Applications
Verlag: Springer Berlin Heidelberg
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In this paper, we present a robust and accurate method for the segmentation of cross-sectional boundaries of vessels found in contrast-enhanced images. The proposed algorithm first detects the edges along 1D rays in multiple scales by using mean-shift analysis. Second, edges from different scales are accurately and efficiently combined by using the properties of mean-shift clustering. Third, boundaries of vessel cross-sections are obtained by using local and global perceptual edge grouping and elliptical shape verification. The proposed algorithm is stable to (
i
) the case where the vessel is surrounded by other vessels or other high contrast structures, (
iii
) contrast variations in vessel boundary, and (
iii
) variations in the vessel size and shape. The accuracy of the algorithm is shown on several examples.