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Enhanced Chimp Optimization Algorithm Using attack defense strategy and Golden Update Mechanism for Robust COVID-19 Medical Image Segmentation

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Journal of Bionic Engineering 2024年第4期21卷 2086-2109页

作者： Amir Hamza Morad Grimes Abdelkrim Boukabou Samira Dib Non Testing Destructive Laboratory Faculty of TechnologyUniversity of Jijel18000JijelAlgeria Laboratory of Renewable Energy Faculty of TechnologyUniversity of Jijel18000JijelAlgeria

Medical image segmentation is a powerful and evolving technology in medical *** fact,it has been identified as a very effective tool to support and accompany doctors in their fight against the spread of the coronavirus(COVID-19).Various techniques have been utilized for COVID-19 image segmentation,including Multilevel Thresholding(MLT)-based meta-heuristics,which are considered crucial in addressing this ***,despite their importance,meta-heuristics have significant ***,the imbalance between exploration and exploitation,as well as premature convergence,can cause the optimization process to become stuck in local optima,resulting in unsatisfactory segmentation *** this paper,an enhanced War strategy Chimp Optimization Algorithm(WSChOA)is proposed to address MLT *** strategies are incorporated into the traditional Chimp Optimization *** update mechanism that provides diversity in the ***,the attack and defense strategies are incorporated to improve the search space leading to avoiding local *** experimental results were conducted by comparing WSChoA with recent and well-known algorithms using various evaluation metrics such as Feature Similarity Index(FSIM),Structural Similarity Index(SSIM),Peak signal-to-Noise Ratio(PSNR),Standard deviation(STD),Freidman Test(FT),and Wilcoxon Sign Rank Test(WSRT).The results obtained by WSChoA surpassed those of other optimization techniques in terms of robustness and accuracy,indicating that it is a powerful tool for image segmentation.

关键词： Image processing Segmentation Optimization Chimp Golden update mechanism attack-defense strategy COVID-19

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