title: Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm.
abstract: The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method.
authors.affiliation: School of Information and Engineering, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China.
authors.forename: Zhang
authors.initials: Z
authors.lastname: Yang
authors.affiliation: Zhejiang ZhongLan Environment Technology Ltd., Wenzhou, Zhejiang 325000, China.
authors.forename: Ye
authors.identifier: 0000-0003-2472-8461
authors.initials: Y
authors.lastname: Shufan
authors.affiliation: School of Medical Imaging, Tianjin Medical University, Wenzhou, Zhejiang 300000, China.
authors.forename: Guo
authors.initials: G
authors.lastname: Li
authors.affiliation: 118 Hospital of the People's Liberation Army, Wenzhou, Zhejiang 325000, China.
authors.forename: Ding
authors.initials: D
authors.lastname: Weifeng
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D017143:Fuzzy Logic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D059906:Neuroimaging / Q000706:statistics & numerical data*