脑磁共振图像中噪声水平的估计

Maria G. Pereza, Aura Concib, Ana Belen Morenoc, Victor H. Andaluza, J. A. Hernándezd
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引用次数: 7

摘要

为了进行有效的分析,图像中噪声水平的估计对于每个模态的具体估计非常重要。此外,它是许多图像处理方法的基本步骤和不可缺少的程序。特别是在磁共振图像(MRI)中由于出现了这些噪声,因此必须对其噪声水平进行评估。本文提出了一种估计MR图像T1-w噪声水平的新方法,并与已知的信噪比水平进行了比较。这样做的优点是易于在图像采集过程中使用,当然还有身体其他部位的适应性。评估的正确性是通过对Atlas无噪声图像的比较来解决的,其中人为添加和已知的噪声水平。其主要思想是在配准后对相同的切片进行匹配,以评估噪声的水平。为了评估图像中的噪声范围,我们使用了信噪比- SNR和一组具有不断增加的噪声水平的MRI。然而,其他指标,如归一化相互关系- NCC或均方根误差(RMSE)也可以使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating the Rician noise level in brain MR image
For an efficient analysis the estimation of the noise level in images is very important to specific estimates of each modality. Moreover, it is a fundamental step and indispensable procedure for a number of image processing approaches. Especially in magnetic resonance images (MRI) due to the Rician presented in these, where the level of noise must be evaluated. In this paper a new method to estimate the noise level in MR images T1-w is proposed and compared with a known level of the ration of signal and noise presented. The advantage of this is its easiness for utilization during image acquisition and of course the adaptability of the idea of other areas of body. The correctness of the evaluation is addressed by comparison of Atlas noise free images where the level of Rician noise was artificially added and known. The main idea is the matching of same slices after registration in order to evaluate the level of noise. For evaluation of the range of noise in an image we used the signal noise ratio - SNR and a set of MRI with increasing levels of Rician noise. However, others metrics like the normalized cross correlation - NCC or the Root Mean Squared Error (RMSE) could be used as well.
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