一种新的脑MRI降噪方法

SEVENTH INTERNATIONAL SYMPOSIUM ON NEGATIVE IONS, BEAMS AND SOURCES (NIBS 2020) Pub Date : 2021-07-30 DOI:10.1063/5.0058059

G. Devi, S. Velliangiri, S. Alagumuthukrishnan

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引用次数: 0

摘要

本文提出了一种基于对偶树cwt和非局部均值滤波的脑磁共振图像去噪算法。降噪采用两阶段过程，首先应用稀疏DT-CWT，该方法允许在变换空间中区分数据的方向性，然后应用非局部均值滤波器的旋转不变版本。用不同噪声水平的脑磁共振图像对该算法进行了测试。在噪声降低15%的情况下，得到的PSNR和SSIM分别为23dB和0.93，优于各向异性扩散滤波(ADF)、非局部极大似然滤波(NLML)和营养集中值滤波(NS Median)。

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A novel implementation for brain MRI noise reduction

In this paper proposed algorithm is based on Dual Tree-CWT and Nonlocal Mean filtering processes is used to eliminate Rician noise from the brain magnetic resonance images. The noise reduction is done using two stage processes, first sparse DT-CWT is applied, which allows for distinction of data directionality in the transform space and then Rotational invariant version of Non-Local Mean filter is applied. The proposed algorithm is tested with different Rician noise levels of brain MR Images. Even the Image is degraded by 15% Rician noise the PSNR and SSIM obtained are 23dB and 0.93 which is a better performance as compared to Anisotropic Diffusion Filter (ADF), Non local Maximum Likelihood (NLML), Nutrosophic Set Median Filter (NS median).

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来源期刊

SEVENTH INTERNATIONAL SYMPOSIUM ON NEGATIVE IONS, BEAMS AND SOURCES (NIBS 2020)

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