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    Image Segmentation of Brain MR Images Using Otsu’s Based Hybrid WCMFO Algorithm

    A. Renugambal1, *, K. Selva Bhuvaneswari2

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 681-700, 2020, DOI:10.32604/cmc.2020.09519

    Abstract In this study, a novel hybrid Water Cycle Moth-Flame Optimization (WCMFO) algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance (MR) image slices. WCMFO constitutes a hybrid between the two techniques, comprising the water cycle and moth-flame optimization algorithms. The optimal thresholds are obtained by maximizing the between class variance (Otsu’s function) of the image. To test the performance of threshold searching process, the proposed algorithm has been evaluated on standard benchmark of ten axial T2-weighted brain MR images for image segmentation. The experimental outcomes infer that it produces better optimal threshold values… More >

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