Brain Tumor Detection Through Modified Optimization Algorithm by Region-based Image Fusion
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Abstract
This article is about the fusion of Brain images which are having different features. This article addresses the problems raised in pixel-level image fusion,such as blurring and artifacts caused by the unwanted addition of noise components in fused images. We extracted the regions of the brain image with the proposed tested optimal thresholding-based segmentation by optimizing thresholds with the proposed Sine function adapted improved Whale Optimization Algorithm (SiWOA) algorithm. We named the proposed fusion as SiWOA-FUSION. These optimal segmented regions and discrete wavelet coefficients of images are fused based on interval type - 2 fuzzy rules. Finally, combined image visual quality is optimized with SiWOA by assuming the amount of the correlation of differences (ACD) as an objective function. Experiments are tested on standard benchmark databases and proved better than existing methods.
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