Adaptive fixed-point iterative shrinkage/thresholding algorithm for MR imaging reconstruction using compressed sensing

Recently compressed sensing (CS) has been applied to under-sampling MR image reconstruction for significantly reducing signal acquisition time. To guarantee the accuracy and efficiency of the CS-based MR image reconstruction, it necessitates determining several regularization and algorithm-introduce...

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Veröffentlicht in:	Magnetic resonance imaging Jg. 32; H. 4; S. 372 - 378
Hauptverfasser:	Wu, Geming, Luo, Shuqian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier Inc 01.05.2014
Schlagworte:	Algorithms Brain - anatomy & histology Compressed sensing Data Compression - methods Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Magnetic resonance imaging Magnetic Resonance Imaging - methods Non-linear reconstruction Numerical Analysis, Computer-Assisted Radiology Regularization parameter Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Non-linear reconstruction Magnetic resonance imaging Regularization parameter Compressed sensing
ISSN:	0730-725X, 1873-5894, 1873-5894
Online-Zugang:	Volltext
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