Abstract
This paper introduces a combination method for blood vessel segmentation based on k-means clustering and morphological thinning. In the first stage, the original image was partitioned into two clusters (foreground and background). As this step is a coarse classification, a fine detection proceeded to the pre-processed image with the help of the morphological thinning algorithm. Experimental results indicated that blood vessels within an image have been detected by using the coarse-to-fine segmentation method with the accuracy of more than 90%.
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Luo, Z., Liu, Z., Li, J. (2011). Micro-Blood Vessel Detection Using K-means Clustering and Morphological Thinning. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21111-9_39
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DOI: https://doi.org/10.1007/978-3-642-21111-9_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21110-2
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