Simultaneuos Magnitude and Phase Regularization in MR Compressed Sensing using Multi-frame FREBAS Transform

It is difficults to apply CS to images with rapid spatial phase variations, since not only the magnitude but also phase regularization is required in the CS framework. An iterative MRI reconstruction with separate magnitude and phase regularization was proposed for applications where magnitude and phase maps are both of interest. Since this method requires the approximation of phase regularizer to cope with phase unwrapping problem, it is roughly 10 times slower than conventional CS and the convergence is not guaranteed. In this article we propose a novel image reconstruction scheme for CS-MRI in which phase regularizer or symmetrical sampling trajectory are not required in the rather standard CS reconstruction scheme, but highly robust to rapid phase changes. The proposed method uses multi-frame complex transforms to introduce sparseness for the complex image data.

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