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Adaptive SNR filtering technique for Rician noise denoising in MRI

机译:MRI中RICIAN噪声去噪的自适应SNR过滤技术

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MRI images are affected by Rician noise due to the magnitude image formation. Presence of Rician noise can significantly affect the image quality and contrast ratio of an image. In this paper we propose an adaptive filtering technique for Rician noise. Rician noise displays varying distribution characteristic depending on the SNR of the image. Based on the probability distribution function of noise and SNR information obtained from the image, the proposed filter uses local statistics of the neighborhood within the mask to perform denoising. The filter thus performs adaptive denoising based on the regional SNR of the neighborhood. The proposed filtering technique has been implemented on synthetic image and T2 weighted magnitude MRI images. The efficiency of the proposed filtering technique is verified with a study of the PSNR, MSSIM and RMSE characteristic of the denoised and noisy image with respect to the true image. The proposed denoising technique shows an improvement in the contrast ratio and PSNR of the noisy image.
机译:由于幅度图像形成,MRI图像受瑞典噪声的影响。瑞典噪声的存在可以显着影响图像的图像质量和对比度。在本文中,我们提出了一种用于瑞典噪声的自适应过滤技术。瑞典噪音根据图像的SNR显示不同的分布特性。基于从图像获得的噪声和SNR信息的概率分布函数,所提出的滤波器使用掩码内邻域的局部统计来执行去噪。因此,过滤器基于邻域的区域SNR执行自适应去噪。所提出的滤波技术已经在合成图像和T2加权幅度MRI图像上实现。通过关于真实图像的PSNR,MSSIM和RMSE特性的研究验证了所提出的滤波技术的效率。所提出的去噪技术表明了噪声图像的对比度和PSNR的改善。

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