Abstract #2882

Variable-Density Parallel Imaging with Partially Localized Coil Sensitivities

Tolga ukur¹, Juan Santos¹, John Pauly¹, Dwight Nishimura¹

¹Department of Electrical Engineering, Stanford University, Stanford, CA, United States

PILS is a very fast reconstruction method for both Cartesian and non-Cartesian sampling; however, it can suffer from residual aliasing artifacts when coupled with variable-density acquisitions. In this work, we propose an improved variable-FOV method that suppresses the aliasing artifacts, while optimally utilizing the densely sampled low-spatial-frequency data. Individual coil images are then linearly combined using data-driven sensitivity estimates. In vivo comparisons with PILS and SENSE are provided.