期刊
INTERNATIONAL JOURNAL OF APPLIED METAHEURISTIC COMPUTING
卷 10, 期 3, 页码 91-106出版社
IGI GLOBAL
DOI: 10.4018/IJAMC.2019070105
关键词
Anisotropic Diffusion; Bacterial Foraging Optimization; MR Image Segmentation; Multilevel Thresholding; Otsu Method; Particle Swarm Optimization
Multilevel thresholding is widely used in brain magnetic resonance (MR) image segmentation. In this article, a multilevel thresholding-based brain MR image segmentation technique is proposed. The image is first filtered using anisotropic diffusion. Then multilevel thresholding based on particle swarm optimization (PSO) is performed on the filtered image to get the final segmented image. Otsu function is used to select the thresholds. The proposed technique is compared with standard PSO and bacterial foraging optimization (BFO) based multilevel thresholding techniques. The objective image quality metrics such as Peak Signal to Noise Ratio (PSNR) and Mean Structural SIMilarity (MSSIM) index are used to evaluate the quality of the segmented images. The experimental results suggest that the proposed technique gives significantly better-quality image segmentation compared to the other techniques when applied to T2-weitghted brain MR images.
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