A two-stage low rank approach for calibrationless dynamic parallel magnetic resonance image reconstruction

DOI10.1007/s10915-016-0225-6zbMath1371.65019OpenAlexW2465095684MaRDI QIDQ2399228

Xiaoqun Zhang, Likun Hou, Hao Gao

Publication date: 22 August 2017

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-016-0225-6

zbMATH Keywords

numerical experimentsforward-backward splitting methoddynamic magnetic resonance imagingauto-calibration signalsimage sequence reconstructionlow rank plus sparsitysensitivity maps estimation

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Parallel numerical computation (65Y05)

Cites Work

• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• An Accelerated Proximal Gradient Algorithm for Frame-Based Image Restoration via the Balanced Approach
• A Singular Value Thresholding Algorithm for Matrix Completion
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Dynamic SPECT reconstruction from few projections: a sparsity enforced matrix factorization approach
• Signal Recovery by Proximal Forward-Backward Splitting

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