Abstract
Serious types of vascular diseases such as carotid stenosis, aneurysm and vascular malformation may lead to brain stroke, which are the third leading cause of death and the number one cause of disability. In the clinical practice of diagnosis and treatment of cerebral vascular diseases, how to do effective detection and description of the vascular structure of two-dimensional angiography sequence image that is blood vessel skeleton extraction has been a difficult study for a long time. This paper mainly discussed two-dimensional image of blood vessel skeleton extraction based on the level set method, first do the preprocessing to the DSA image, namely uses anti-concentration diffusion model for the effective enhancement and uses improved Otsu local threshold segmentation technology based on regional division for the image binarization, then vascular skeleton extraction based on GMM (Group marching method) with fast sweeping theory was actualized. Experiments show that our approach not only improved the time complexity, but also make a good extraction results.
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Xu, J., Wu, J., Feng, D., Cui, Z. (2009). DSA Image Blood Vessel Skeleton Extraction Based on Anti-concentration Diffusion and Level Set Method. In: Cai, Z., Li, Z., Kang, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2009. Communications in Computer and Information Science, vol 51. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04962-0_22
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DOI: https://doi.org/10.1007/978-3-642-04962-0_22
Publisher Name: Springer, Berlin, Heidelberg
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