Dynamic Magnetic Resonance Imaging Reconstruction Using Parallel Temporal Gradient Filtering

2017 ◽  
Vol 7 (1) ◽  
pp. 258-263
Author(s):  
Yang Wang ◽  
Ning Cao ◽  
Yudong Zhang ◽  
Bin Guo
2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Lixia Chen ◽  
Bin Yang ◽  
Xuewen Wang

The quality of dynamic magnetic resonance imaging reconstruction has heavy impact on clinical diagnosis. In this paper, we propose a new reconstructive algorithm based on the L+S model. In the algorithm, the l1 norm is substituted by the lp norm to approximate the l0 norm; thus the accuracy of the solution is improved. We apply an alternate iteration method to solve the resulting problem of the proposed method. Experiments on nine data sets show that the proposed algorithm can effectively reconstruct dynamic magnetic resonance images.


2009 ◽  
Vol 115 (2) ◽  
pp. 287-300 ◽  
Author(s):  
M.C. Martina ◽  
P.P. Campanino ◽  
F. Caraffo ◽  
C. Marcuccio ◽  
F. Gunetti ◽  
...  

2019 ◽  
Vol 84 ◽  
pp. 368-374
Author(s):  
Magdalena Derlatka-Kochel ◽  
Pawel Kumoniewski ◽  
Marcin Majos ◽  
Kamil Ludwisiak ◽  
Lech Pomorski ◽  
...  

2020 ◽  
Vol 0 (0) ◽  
pp. 1-16
Author(s):  
Shanshan Wang ◽  
◽  
Yanxia Chen ◽  
Taohui Xiao ◽  
Lei Zhang ◽  
...  

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