医学图像去噪的增强BE-GGMM-EI算法

K. C. Patra, M. Panigrahi, Sushil Kumar Mahapatra, Minu Samantaray
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引用次数: 1

摘要

如今,不丢失边缘信息的脑肿瘤检测是非常重要的研究领域,它可以挽救许多人的生命。因此,在我们提出的方法中,我们着重于最小化脑肿瘤MRI图像的信息丢失。为此,我们提出了一种BE-GGMM-EI(带边缘信息的背景估计-广义高斯混合模型)检测不同脑肿瘤的方法。该方法首先对肿瘤MRI图像进行背景减法处理,然后利用边缘最大化技术对边缘进行增强处理。然后对图像进行GGMM去噪。实验结果表明,该方法具有较好的边缘信息和较好的PSNR值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Enhanced BE-GGMM-EI Algorithm for Medical Image Denoising
Now a days, brain tumor detection without losing the edge information is very vital field of research, which may save many life. So in our proposed method, we have given emphasis on minimum loss of information in brain tumor MRI image. So we propose a BE-GGMM-EI (Background Estimated-Generalized Gaussian Mixture Model with Edge Information) method for detecting different brain tumors. In our proposed method, the tumor MRI image is first processed for background subtraction then the edge is enhanced with edge maximization technique. After that the image is denoised GGMM. Experimental results authenticate our proposed GGMM method to have better edge information with good PSNR value.
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