旋转不变的非局域均值算法在磁共振图像去噪中的应用

doi:10.11938/cjmr20172582

波谱学杂志 ›› 2018, Vol. 35 ›› Issue (2): 162-169.doi: 10.11938/cjmr20172582

旋转不变的非局域均值算法在磁共振图像去噪中的应用

张波¹, 谢海滨^1,2, 严序³, 李文静¹, 杨光^1,2

1. 华东师范大学物理与材料科学学院, 上海磁共振重点实验室, 上海 200062;
2. 上海卡勒幅磁共振技术有限公司, 上海 200062;
3. 西门子医疗东北亚科研合作部, 上海 201318

收稿日期:2017-05-26 出版日期:2018-06-05 发布日期:2018-05-29
通讯作者: 谢海滨,Tel:021-62233873,E-mail:hbxie@phy.ecnu.edu.cn E-mail:hbxie@phy.ecnu.edu.cn
基金资助:
国家高技术研究发展计划资助项目（2014AA123400）.

Rotation Invariant Non-Local Means for Noise Reduction in Magnetic Resonance Images

ZHANG Bo¹, XIE Hai-bin^1,2, YAN Xu³, LI Wen-jing¹, YANG Guang^1,2

1. Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, Shanghai 200062, China;
2. Shanghai Colorful Magnetic Resonance Technology Co., Ltd., Shanghai 200062, China;
3. MR Collaboration NE Asia, Siemens Healthcare, Shanghai 201318, China

Received:2017-05-26 Online:2018-06-05 Published:2018-05-29

摘要/Abstract

摘要： 磁共振成像（MRI）实验时常采用多次扫描累加平均提高图像信噪比（SNR），但当扫描过程中运动引起图像变形时，简单地累加平均就无法奏效.为此，本研究组曾提出一种匹配加权平均方法（MWA）提高图像的信噪比.在此基础上，该文提出一种旋转不变的非局域均值算法（RINLM），即选取圆形邻域区域并将其划分为一系列以中心像素为圆心的等面积圆环，再计算模式的相似性.RINLM算法可以更好地利用图像中旋转的冗余信息、找到更多的相似结构，提高算法的去噪性能.我们把该方法应用于低信噪比图像序列的平均和去噪中，可以更好地处理旋转的局部运动.与非局域均值算法（NLM）相比，RINLM算法可以进一步提高图像的信噪比；与MWA方法相比，其与RINLM算法的结合可以进一步提高磁共振图像序列信噪比，更好的保持图像边缘信息.

关键词: 磁共振成像(MRI), 非局域均值算法(NLM), 旋转不变性, 图像去噪

Abstract: Averaging of multiple scans is often used in magnetic resonance imaging (MRI) to increase the signal-to-noise ratio (SNR). However, image averaging often results in movement-induced blurs of the edges and tissue details. A matched and weighted averaging (MWA) method has been proposed by our group to obtain images with reduced blurring effects in signal averaging. Here a rotation-invariant non-local means (RINLM) algorithm was proposed, which used circular patches consisted of series of rings with equal area, instead of square patches, to search for similar patches in the images. Compared with the non-local means (NLM) algorithm, the RINLM algorithm was capable of finding more similar patches in the images containing many rotated local structure. This method was used to process noisy images to improve the SNR, and validated using both phantom images and in vivo MR images. The results demonstrated that the method could improve the SNR, while better preserving the edges and details of the images.

Key words: magnetic resonance imaging (MRI), non-local means (NLM), rotation invariance, image denoising

中图分类号:

O482.53

张波, 谢海滨, 严序, 李文静, 杨光. 旋转不变的非局域均值算法在磁共振图像去噪中的应用[J]. 波谱学杂志, 2018, 35(2): 162-169.

ZHANG Bo, XIE Hai-bin, YAN Xu, LI Wen-jing, YANG Guang. Rotation Invariant Non-Local Means for Noise Reduction in Magnetic Resonance Images[J]. Chinese Journal of Magnetic Resonance, 2018, 35(2): 162-169.

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旋转不变的非局域均值算法在磁共振图像去噪中的应用

Rotation Invariant Non-Local Means for Noise Reduction in Magnetic Resonance Images

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