The Research of MRI Reconstruction Method by Using Weighted Schatten P-Norm Minimization
JIANG Ming-feng1, LU Liang1, WU Long1, XU Wen-long2, WANG Ya-ming1
1. School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China;
2. Department of Biomedical Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China
摘要 本文提出了一种基于加权Schatten p范数最小化(Weighted Schatten p-Norm Minimization,WSNM)的磁共振图像重构算法,该方法利用磁共振图像的非局部自相似性,并结合Schatten p范数和不同秩元素重要性的加权因子,实现磁共振图像重构过程的低秩约束.此外,采用交替方向乘子算法(Alternating Direction Method of Multipliers,ADMM)来求解基于WSNM磁共振图像重构的非凸最小化问题.实验结果表明,相比于最近的磁共振重构算法,基于WSNM的磁共振图像重构方法具有更好的重建效果,可获得更高的峰值信噪比(Peak Signal to Noise Ratio,PSNR)和更好的结构相似性(Structural Similarity,SSIM).
Abstract:In this paper,the weighted Schatten p-norm minimization (WSNM) method is proposed to implement magnetic resonance imaging (MRI) reconstruction.The nonlocal self-similarity of magnetic resonance images,Schatten p-norm and the weighting factors of the importance of different rank elements are integrated together as the low rank constraint to regularize the MRI reconstruction.In addition,the Alternating Direction Method of Multipliers (ADMM) algorithm is used to solve the non-convex minimization problem of MRI reconstruction based WSNM.Compared with other state-of-the-art methods in numerical experiments,the proposed method achieves a higher reconstruction quality with higher peak signal to noise ratio (PSNR) and better structural similarity (SSIM) index.
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