Fast non-Cartesian L 1 -SPIRiT with Field Inhomogeneity Correction

Fast, undersampled single-shot k-space trajectories have applications in functional and dynamic imaging, but their long readouts cause artifacts in the presence of field inhomogeneity. We propose an extension of a recently developed algorithm for fast L ₁ -SPIRiT reconstruction of undersampled non-Cartesian parallel imaging data, using a system matrix augmented with time-segmentation and a circulant preconditioner to yield high quality images quickly. We compare our method to the existing fast non-Cartesian L ₁ -SPIRiT using both simulated brain and real phantom data sets, where our proposed method effectively eliminates artifacts from field inhomogeneity.

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