Micro-blood vessel detection using K-means clustering and morphological thinning

Authors:
Zhongming Luo;Zhuofu Liu;Junfu Li
Affiliations:
The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province, Harbin University of Science and Technology, Heilongjiang, China;The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province, Harbin University of Science and Technology, Heilongjiang, China;The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province, Harbin University of Science and Technology, Heilongjiang, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Year:
2011

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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%.