scholarly journals Parallel Computing of Patch-Based Nonlocal Operator and Its Application in Compressed Sensing MRI

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Qiyue Li ◽  
Xiaobo Qu ◽  
Yunsong Liu ◽  
Di Guo ◽  
Jing Ye ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Compressed Sensing ◽  
Multicore Processors ◽  
Parallel Architecture ◽  
Computation Time ◽  
Reconstruction Error ◽  
Nonlocal Operator ◽  
Resonance Imaging ◽  
Reconstruction Process

Magnetic resonance imaging has been benefited from compressed sensing in improving imaging speed. But the computation time of compressed sensing magnetic resonance imaging (CS-MRI) is relatively long due to its iterative reconstruction process. Recently, a patch-based nonlocal operator (PANO) has been applied in CS-MRI to significantly reduce the reconstruction error by making use of self-similarity in images. But the two major steps in PANO, learning similarities and performing 3D wavelet transform, require extensive computations. In this paper, a parallel architecture based on multicore processors is proposed to accelerate computations of PANO. Simulation results demonstrate that the acceleration factor approaches the number of CPU cores and overall PANO-based CS-MRI reconstruction can be accomplished in several seconds.

scholarly journals A Novel Compressed Sensing Method for Magnetic Resonance Imaging: Exponential Wavelet Iterative Shrinkage-Thresholding Algorithm with Random Shift

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yudong Zhang ◽  
Jiquan Yang ◽  
Jianfei Yang ◽  
Aijun Liu ◽  
Ping Sun
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Compressed Sensing ◽  
Mean Squared Error ◽  
State Of The Art ◽  
Computation Time ◽  
Resonance Imaging ◽  
Iterative Shrinkage ◽  
Thresholding Algorithm ◽  
Iterative Shrinkage Thresholding

Aim. It can help improve the hospital throughput to accelerate magnetic resonance imaging (MRI) scanning. Patients will benefit from less waiting time.Task. In the last decade, various rapid MRI techniques on the basis of compressed sensing (CS) were proposed. However, both computation time and reconstruction quality of traditional CS-MRI did not meet the requirement of clinical use.Method. In this study, a novel method was proposed with the name of exponential wavelet iterative shrinkage-thresholding algorithm with random shift (abbreviated as EWISTARS). It is composed of three successful components: (i) exponential wavelet transform, (ii) iterative shrinkage-thresholding algorithm, and (iii) random shift.Results. Experimental results validated that, compared to state-of-the-art approaches, EWISTARS obtained the least mean absolute error, the least mean-squared error, and the highest peak signal-to-noise ratio.Conclusion. EWISTARS is superior to state-of-the-art approaches.

scholarly journals An Augmented Lagrangian Based Compressed Sensing Reconstruction for Non-Cartesian Magnetic Resonance Imaging without Gridding and Regridding at Every Iteration

PLoS ONE ◽  
2014 ◽  
Vol 9 (9) ◽  
pp. e107107 ◽  
Author(s):  
Mehmet Akçakaya ◽  
Seunghoon Nam ◽  
Tamer A. Basha ◽  
Keigo Kawaji ◽  
Vahid Tarokh ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Compressed Sensing ◽  
Augmented Lagrangian ◽  
Resonance Imaging

scholarly journals Performance of compressed sensing for fluorine‐19 magnetic resonance imaging at low signal‐to‐noise ratio conditions

2019 ◽  
Vol 84 (2) ◽  
pp. 592-608
Author(s):  
Ludger Starke ◽  
Andreas Pohlmann ◽  
Christian Prinz ◽  
Thoralf Niendorf ◽  
Sonia Waiczies
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Compressed Sensing ◽  
Signal To Noise Ratio ◽  
Resonance Imaging ◽  
Signal To Noise ◽  
Noise Ratio

Improved compressed sensing reconstruction for $$^{19}$$ 19 F magnetic resonance imaging

2019 ◽  
Vol 32 (1) ◽  
pp. 63-77 ◽  
Author(s):  
Thomas Kampf ◽  
Volker J. F. Sturm ◽  
Thomas C. Basse-Lüsebrink ◽  
André Fischer ◽  
Lukas R. Buschle ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Compressed Sensing ◽  
Resonance Imaging
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