Magnetic resonance imaging (MRI) images are frequently sensitive to certain types of noises and artifacts. The denoising of MRI images is essential for improving visual quality and reliability of the quantitative analysis of diagnosis and treatment. In this article, a new block difference‐based filtering method is proposed to denoise the MRI images. First, the normal MRI image is degraded by a certain percentage of noise. The block difference between the intensity of the normal and noisy MRI is computed, and then it is compared with the intensity of the blocks of the normal MRI image. Based on the comparison, the pixel weights are updated to each block of the denoised MRI image. Observational results are brought out on the BrainWeb and BraTS datasets and evaluated by performance metrics such as peak signal‐to‐noise ratio, structural similarity index measures, universal quality index, and root mean square error. The proposed method outperforms the existing denoising filtering techniques.

中文翻译：

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使用基于块差异的滤波方法去除 MRI 图像中的噪声

磁共振成像 (MRI) 图像通常对某些类型的噪声和伪影很敏感。MRI图像去噪对于提高诊断和治疗定量分析的视觉质量和可靠性至关重要。在本文中，提出了一种新的基于块差异的滤波方法来对 MRI 图像进行去噪。首先，正常的 MRI 图像会因一定比例的噪声而退化。计算正常和噪声 MRI 的强度之间的块差异，然后将其与正常 MRI 图像的块强度进行比较。基于比较，像素权重被更新到去噪 MRI 图像的每个块。在 BrainWeb 和 BraTS 数据集上得出观察结果，并通过峰值信噪比等性能指标进行评估，结构相似性指标测量、通用质量指标和均方根误差。所提出的方法优于现有的去噪滤波技术。