FCMLSM Segmentation of Micro-Vessels in Slight Defocused Microscopic Images

To address problems relating to microscopic micro-vessel images of living bodies, including poor vessel continuity, blurry boundaries between vessel edges and tissue and uneven field illuminance, and this paper put forward a fuzzy-clustering level-set segmentation algorithm. By this method, pre-trea...

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Vydáno v:Journal of advanced computational intelligence and intelligent informatics Ročník 23; číslo 6; s. 1073 - 1079
Hlavní autoři: Luo, Zhongming, Zhang, Yu, Zhou, Zixuan, Bi, Xuan, Wu, Haibin, Xin, Zhentao
Médium: Journal Article
Jazyk:angličtina
Vydáno: 20.11.2019
ISSN:1343-0130, 1883-8014
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Abstract To address problems relating to microscopic micro-vessel images of living bodies, including poor vessel continuity, blurry boundaries between vessel edges and tissue and uneven field illuminance, and this paper put forward a fuzzy-clustering level-set segmentation algorithm. By this method, pre-treated micro-vessel images were segmented by the fuzzy c-means (FCM) clustering algorithm to obtain original contours of interesting areas in images. By the evolution equations of the improved level set function, accurate segmentation of microscopic micro-vessel images was realized. This method can effectively solve the problem of manual initialization of contours, avoid the sensitivity to initialization and improve the accuracy of level-set segmentation. The experiment results indicate that compared with traditional micro-vessel image segmentation algorithms, this algorithm is of high efficiency, good noise immunity and accurate image segmentation.
AbstractList To address problems relating to microscopic micro-vessel images of living bodies, including poor vessel continuity, blurry boundaries between vessel edges and tissue and uneven field illuminance, and this paper put forward a fuzzy-clustering level-set segmentation algorithm. By this method, pre-treated micro-vessel images were segmented by the fuzzy c-means (FCM) clustering algorithm to obtain original contours of interesting areas in images. By the evolution equations of the improved level set function, accurate segmentation of microscopic micro-vessel images was realized. This method can effectively solve the problem of manual initialization of contours, avoid the sensitivity to initialization and improve the accuracy of level-set segmentation. The experiment results indicate that compared with traditional micro-vessel image segmentation algorithms, this algorithm is of high efficiency, good noise immunity and accurate image segmentation.
Author Bi, Xuan
Luo, Zhongming
Zhou, Zixuan
Xin, Zhentao
Wu, Haibin
Zhang, Yu
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The Higher Educational Key Laboratory for Measuring and Control Technology and Instrumentations of Heilongjiang Province, National Experimental Teaching Demonstration Center of Measuring and Control Technology, Harbin University of Science and Technology No.52, Xuefu Road, Nangang District, Harbin, Heilongjiang 150080, China
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