The Research of MRI Reconstruction Method by Using Weighted Schatten P-Norm Minimization

被引：0
|
作者：
Jiang M.-F. [1 ]
Lu L. [1 ]
Wu L. [1 ]
Xu W.-L. [2 ]
Wang Y.-M. [1 ]
机构：
[1] School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, Zhejiang
[2] Department of Biomedical Engineering, China Jiliang University, Hangzhou, 310018, Zhejiang
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2019年 / 47卷 / 04期
关键词：
Magnetic resonance imaging (MRI) reconstruction; Nonlocal self-similarity; Weighted Schatten p-norm minimization;
D O I：
10.3969/j.issn.0372-2112.2019.04.003
中图分类号：
学科分类号：
摘要：
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. © 2019, Chinese Institute of Electronics. All right reserved.
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页码：784 / 790
页数：6
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