Abstract
A novel multi-resolution approach is presented for vessel segmentation using multi-scale fuzzy clustering and vessel enhancement filtering. According to geometric shape analysis of the vessel structure with different scale, a new fuzzy inter-scale constraint based on antistrophic diffusion linkage model is introduced which builds an efficient linkage relationship between the high resolution feature images and low resolution ones. Meanwhile, this paper develops two new fuzzy distances which describe the fuzzy similarity of line-like structure in adjacent scales effectively. Moreover, a new multiresolution framework combining the inter- and intra-scale constraints is presented. The proposed framework is robust to noisy vessel images and low contrast ones, such as medical images. Segmentation of a number of vessel images shows that the proposed approach is robust and accurate.
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Yu, G., Lin, P., Cai, S. (2008). Robust Vessel Segmentation Based on Multi-resolution Fuzzy Clustering. In: Fyfe, C., Kim, D., Lee, SY., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2008. IDEAL 2008. Lecture Notes in Computer Science, vol 5326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88906-9_43
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DOI: https://doi.org/10.1007/978-3-540-88906-9_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88905-2
Online ISBN: 978-3-540-88906-9
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