Denoising techniques for multi-parametric prostate MRI: A Comparative Study

A. Latrach, Rania Trigui, Lamia Sellemi
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Abstract

Since recent years, denoising become one Of the most active area of research in image processing topic. Usually, MR images are affected by noise and artifacts during the acquisition process. Therefore, many denoising algorithms have been developed although noise elimination still an undefended challenge. In this paper, we study firstly different denoising filters for T2-Weighted prostate cancer MR images, in order to select the appropriate filter. As example of denoising filters, homomorphic, Median, Wavelet, nonlocal means, gaussian, Anisotropic, Laplacian, Cure-LET, LMMSE and bilateral. Then, we discuss the problem of evaluation of image quality which become necessary. As example of evaluation metrics, we present the PSNR, MSE and SSIM. We consider both subjective and objective quality assessment parameters for determining a final score of filters executed over 40 T2-Weighted MR images. This study concludes that Anisotropic filter should be opted for denoising T2-Weighted MR image since its details preserving capability.
多参数前列腺MRI去噪技术的比较研究
近年来,去噪成为图像处理中最活跃的研究领域之一。通常,磁共振图像在采集过程中会受到噪声和伪影的影响。因此,尽管噪声消除仍然是一个不可避免的挑战,但许多去噪算法已经被开发出来。本文首先研究了不同的t2加权前列腺癌MR图像去噪滤波器,以选择合适的滤波器。作为去噪滤波器的例子,同态滤波器、中值滤波器、小波滤波器、非局部均值滤波器、高斯滤波器、各向异性滤波器、拉普拉斯滤波器、Cure-LET滤波器、LMMSE滤波器和双边滤波器。在此基础上,讨论了图像质量评价问题。作为评估指标的例子,我们提出了PSNR, MSE和SSIM。我们考虑主观和客观的质量评估参数,以确定在40张t2加权MR图像上执行的过滤器的最终分数。本研究认为,各向异性滤波器具有良好的细节保留能力,适合用于t2加权MR图像的去噪。
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