基于偏微分方程的脑MRI图像ROF滤波

S. Jansi, P. Subashini
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引用次数: 3

摘要

图像去噪是医学图像处理和计算机视觉领域的重要内容。图像去噪仍然是研究人员面临的一个挑战,因为去噪会产生伪影,也是图像模糊的主要来源。本文提出了四种不同的方法来降低MRI图像中的图像伪影和噪声,并将偏微分方程(PDE)应用于ROF滤波器以获得更好的MRI脑图像效果。基于错误率和图像质量对现有方法进行了比较和估计。所提出的去噪技术的效率是通过使用定量性能和图像的视觉质量来衡量的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Partial differential equation based ROF filter for MRI brain images
Image denoising is an important in the field of medical image processing and computer vision. Image denoising continues a challenge for researchers because noise removal gives artifacts and the main source for blurring of the images. In this work four different methods are proposed to reduce the image artifacts and noise in the MRI images and also Partial Differential Equations (PDE) is applied to ROF filter to get better results in MRI brain images. The existing methods are compared and estimated based on the error rate and their quality of the image. The efficiency of the proposed denoising technique is measured by using quantitative performance and in terms of visual quality of the images.
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