MR image reconstruction of a regularly undersampled signal using quadratic phase scrambling

In this paper, we propose a new fast image reconstruction method in which a regularly undersampled signal is used instead of random sampling, as is used in compressed sensing (CS). To diffuse the aliasing artifact caused by under-sampling, we adopt phase-scrambling Fourier transform imaging. The proposed method has an advantage over CS in that the quality of the image does not depend on the selection of the sampling trajectory. Simulation studies and experiments show that the proposed method has almost the same peak signal-to-noise ratio as that of a compressed sensing reconstruction.