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A splitting Bregman-based compressed-sensing (CS) approach (CS-SplitBerg), using the nonuniform fast Fourier transform, is proposed to reconstruct radial magnetic resonance (MR) images from undersampled $k$- space measurements. Using the splitting Bregman framework, the proposed CS-SplitBerg approach takes fully into account the measurement noise and exploits the combined sparsity of MR images, i...
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