Comparison of reconstruction algorithm for compressive sensing magnetic resonance imaging
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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.
Keywordscompressed sensing magnetic resonance imaging iterative shrinkage/threshold algorithm exponential wavelet transform
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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