文章基本信息

标题：A Hybrid Approach for Detection of Brain Tumor with Levy Flight Cuckoo Search
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作者：Ravendra Singh ; Bharat Bhushan Agarwal
期刊名称：Webology
印刷版ISSN：1735-188X
出版年度：2022
卷号：19
期号：1
页码：5388-5401
DOI：10.14704/WEB/V19I1/WEB19361
语种：English
出版社：University of Tehran
摘要：The identification and segmentation of tumors in the human brain MRI are very difficult and time-consuming tasks. In the segmentation process, the optimum threshold value is obtained by the methods called Otsuâ€™s and Kapur entropy. The objective functions of these methods are computed using the Cuckoo-McCulloch procedure with levy flight for its accuracy and computational time. In this study, the proposed method incorporating McCullochâ€™s method for the levy-flight generation which is a computationally efficient image segmentation algorithm, the proposed method has compared the performance of efficient CS with Mantegnaâ€™s method. The overall-performance of an efficient CS algorithm is also compared and discussed with other popular methods and also the proposed efficient CS method is prominent and computationally efficient for magnetic resonance imaging. Experimental results encourage related researches in image processing, computer vision.
关键词：Meta-heuristic algorithms;Thresholding;Segmentation;Levy Flight