Approximate Sparsity and Nonlocal Total Variation Based Compressive MR Image Reconstruction
Joint Authors
Tian, Wei
Wang, Shengqian
Hu, Saifeng
Deng, Chengzhi
Wu, Zhaoming
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-28
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Recent developments in compressive sensing (CS) show that it is possible to accurately reconstruct the magnetic resonance (MR) image from undersampled k -space data by solving nonsmooth convex optimization problems, which therefore significantly reduce the scanning time.
In this paper, we propose a new MR image reconstruction method based on a compound regularization model associated with the nonlocal total variation (NLTV) and the wavelet approximate sparsity.
Nonlocal total variation can restore periodic textures and local geometric information better than total variation.
The wavelet approximate sparsity achieves more accurate sparse reconstruction than fixed wavelet l 0 and l 1 norm.
Furthermore, a variable splitting and augmented Lagrangian algorithm is presented to solve the proposed minimization problem.
Experimental results on MR image reconstruction demonstrate that the proposed method outperforms many existing MR image reconstruction methods both in quantitative and in visual quality assessment.
American Psychological Association (APA)
Deng, Chengzhi& Wang, Shengqian& Tian, Wei& Wu, Zhaoming& Hu, Saifeng. 2014. Approximate Sparsity and Nonlocal Total Variation Based Compressive MR Image Reconstruction. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1046337
Modern Language Association (MLA)
Deng, Chengzhi…[et al.]. Approximate Sparsity and Nonlocal Total Variation Based Compressive MR Image Reconstruction. Mathematical Problems in Engineering No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1046337
American Medical Association (AMA)
Deng, Chengzhi& Wang, Shengqian& Tian, Wei& Wu, Zhaoming& Hu, Saifeng. Approximate Sparsity and Nonlocal Total Variation Based Compressive MR Image Reconstruction. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1046337
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1046337