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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Vydané v:	Magnetic resonance imaging Ročník 32; číslo 4; s. 372 - 378
Hlavní autori:	Wu, Geming, Luo, Shuqian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Netherlands Elsevier Inc 01.05.2014
Predmet:	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
On-line prístup:	Získať plný text
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