Name
Title | ||
|---|---|---|
A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization |
Abstract | ||
|---|---|---|
Compressive Sensing Magnetic Resonance Imaging (CSMRI) exploits sparsity of medical images to reconstruct them accurately from undersampled k-space data. In this paper, we propose a novel patch-based nonlocal MRI reconstruction algorithm with low-rank regularization to exploit the structural sparsity of the observed data. In the proposed algorithm, the low-rank regularization is transformed into the nuclear norm minimization problem then the problem is solved by the Singular Value Thresholding (SVT) method with adaptive thresholds estimation and the Alternative Direction Multiplier Method(ADMM). Experimental results show the proposed MRI reconstruction method outperforms many existing algorithms in CSMRI. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/GlobalSIP.2015.7418225 | 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP) |
Keywords | Field | DocType |
Compressed sensing,MRI reconstruction,nonlocal,low rank,alternative direction multiplier method | Iterative reconstruction,Computer vision,Medical imaging,Multiplier method,Algorithm,Reconstruction algorithm,Regularization (mathematics),Linear programming,Artificial intelligence,Real-time MRI,Compressed sensing,Mathematics | Conference |
Citations | PageRank | References |
2 | 0.36 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liyan Sun | 1 | 7 | 3.16 |
| Jinchu Chen | 2 | 2 | 0.70 |
| Delu Zeng | 3 | 164 | 11.46 |
| Xinghao Ding | 4 | 591 | 52.95 |