中国医疗设备2025，Vol.40Issue(2)：35-39,66,6.DOI:10.3969/j.issn.1674-1633.20241267
基于非局部均值与线性最小均方误差估计的MRI去噪研究
Study on MRI Denoising Based on NLM and LMMSE Estimation
吴娟 1荆斌 2荆钧尧 3吴斌 1孙娜娜1
作者信息
- 1. 空军军医大学(第四军医大学)唐都医院 信息科,陕西 西安 710032
- 2. 解放军总医院医疗保障中心 医学工程科,北京 100853
- 3. 北方电子研究所 科技发展部,陕西 西安 710100
- 折叠
摘要
Abstract
Objective To propose a Rician noise removal algorithm for magnetic resonance imaging(MRI).Methods Firstly,the noise level of MRI was estimated by local variance statistics,and then the image was restored by linear least mean square error estimation and non-local means filtering.Results The proposed denoising method was verified qualitatively and quantitatively by using simulated brain MRI.The results showed that when the noise variance of the denoising algorithm was 15,the mean square error,peak signal-to-noise ratio and mean signal-to-noise ratio of different slices were 70.07,29.78 dB and 21.95 dB successively,and the results of non-local means filtering were 82.17,29.11 dB and 21.28 dB successively.The results of linear least mean square error estimation were 108.16,27.80 dB and 19.97 dB successively.It could be seen that the proposed algorithm was superior to other algorithms.Compared with the traditional non-local means filtering,the proposed algorithm also had a certain improvement in edge protection and improved the denoising effect of linear least mean square error estimation at high noise levels.Conclusion The algorithm proposed in this paper can effectively realize the restoration of noisy MRI signal and provide a reliable guarantee for the subsequent image processing and application.关键词
磁共振成像(MRI)/去噪/非局部均值/线性最小均方误差/Rician噪声/自适应/迭代Key words
MRI/denoising/non-local means/linear minimum mean square error/Rician noise/self-adaption/iteration分类
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吴娟,荆斌,荆钧尧,吴斌,孙娜娜..基于非局部均值与线性最小均方误差估计的MRI去噪研究[J].中国医疗设备,2025,40(2):35-39,66,6.
