中国科学技术大学学报 ›› 2017, Vol. 47 ›› Issue (8): 674-678.DOI: 10.3969/j.issn.0253-2778.2017.08.006

• 论著 • 上一篇    下一篇

基于非局部拉格朗日乘子的磁共振图像重建

李超,杜宏伟,邱本胜   

  1. 中国科学技术大学电子科学与技术系,安徽合肥 230027
  • 收稿日期:2016-04-12 修回日期:2016-05-24 出版日期:2017-08-31 发布日期:2017-08-31
  • 通讯作者: 杜宏伟
  • 作者简介:李超,男,1986年生,硕士生. 研究方向:磁共振图像重建. E-mail: marklee@mail.ustc.edu.cn

Magnetic resonance image reconstruction based on nonlocal augmented Lagrangian multiplier method

LI Chao, DU Hongwei, QIU Bensheng   

  1. Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, China
  • Received:2016-04-12 Revised:2016-05-24 Online:2017-08-31 Published:2017-08-31

摘要: 由于TV变换会造成阶梯伪影,使其不能很好地恢复磁共振图像(MRI)的细节和纹理.针对这种缺点,提出了在优化模型中引入非局部正则化来改善现有的MR重建算法.该方法以非局部均值(NLM)滤波为基础,利用磁共振图像的自相似特点,可以有效抑制阶梯效应并恢复图像细节.为了克服该正则化在实现方面的复杂性,进一步提出了一种改进的基于非局部拉格朗日乘子的磁共振成像方法(MRNLM),在简化非局部方法的同时提高了MR图像质量.实验结果表明,该算法在提高信噪比和视觉接受方面均有显著提升,并在时间和质量上达到很好的平衡.

关键词: MR图像恢复, 增广拉格朗日乘子, 非局部均值滤波, TV

Abstract: Total variation (TV) is unable to recover the fine details and textures of magnetic resonance(MR) images since it often suffers from staircase artifact. To reduce these drawbacks, an improved TV MR image recovery algorithm is introduced by using nonlocal regularization into the CS optimization problem. The nonlocal regularization is built on nonlocal means (NLM) filtering and takes advantage of self-similarity in images, which helps to suppress the staircase effect and restore the fine details. On account of the complexity in implementing NLM filter, a modified MR imaging method called nonlocal Lagrange multiplier (MRNLM) is proposed to overcome the above shortcomings while boosting MR image quality. Experimental results demonstrate that the proposed algorithm shows significant improvements on the state-of-the-art TV based algorithms in both SNR and visual perception, as well as a fair balance between time and quality.

Key words: MRI recovery, augmented Lagrange multiplier, nonlocal means filter, total variation

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