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


Affiliations
1 Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu 210048, China
2 Department of Supply Chain Management,W. P. Carey School of Business, Arizona State University, P.O. Box 873406, Tempe, AZ 85287, United States
3 Department of Electrical Engineering, The City College of New York, CUNY, New York, NY 10031, United States
 

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 leastmean-squared error, and the highest peak signal-to-noise ratio. Conclusion: EWISTARS is superior to state-of-the-art approaches.
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  • A Novel Compressed Sensing Method for Magnetic Resonance Imaging: Exponential Wavelet Iterative Shrinkage-thresholding Algorithm with Random Shift

Abstract Views: 98  |  PDF Views: 2

Authors

Yudong Zhang
Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu 210048, China
Jiquan Yang
Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu 210048, China
Jianfei Yang
Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu 210048, China
Aijun Liu
Department of Supply Chain Management,W. P. Carey School of Business, Arizona State University, P.O. Box 873406, Tempe, AZ 85287, United States
Ping Sun
Department of Electrical Engineering, The City College of New York, CUNY, New York, NY 10031, United States

Abstract


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 leastmean-squared error, and the highest peak signal-to-noise ratio. Conclusion: EWISTARS is superior to state-of-the-art approaches.