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, Volume 77, Issue 17, pp 22617–22628 | Cite as

Comparison of reconstruction algorithm for compressive sensing magnetic resonance imaging

  • Fanqiang Kong
Article

Abstract

Compressed sensing can reconstruct the undersampled image. The combination of compressed sensing and magnetic resonance imaging is a potential future fast imaging method in hospitals. This study investigated five state-of-the-art reconstruction approaches: iterative shrinkage/threshold algorithm (ISTA), fast ISTA, subband-adaptive ISTA, exponential wavelet transform ISTA, and exponential wavelet ISTA with random search (EWISTARS). The simulation results compared the five algorithms over hand image and shoulder image. Finally, we can observe the EWISTARS obtains the best result.

Keywords

compressed sensing magnetic resonance imaging iterative shrinkage/threshold algorithm exponential wavelet transform 

Notes

Acknowledgments

This work has been supported by National Natural Science Foundation of China (61401200). Moreover, the authors would also like to thank those anonymous reviewers for their helpful comments to improve this paper.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.College of AstronauticsNanjing University of Aeronautics and AstronauticsNanjingChina

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