1Electrical Engineering, The State University of New York at Buffalo, Buffalo, NY, United States, 2Biomedical Engineering, The State University of New York at Buffalo, Buffalo, NY, United States
This abstract presents a novel reconstruction method for parallel imaging
that does not require auto-calibration data. The method formulates the image
reconstruction problem as a multichannel blind deconvolution problem in k-space
where the data are randomly undersampled in all channels. Under this
formulation, the k-spaces of the desired image and coil sensitivities are
jointly recovered by finding a rank-1 matrix subject to the data consistent
constraint. Experimental results demonstrate that the proposed
method is able to achieve better reconstruction results than the
state-of-the-art calibration-less parallel imaging methods.
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