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Abstract #2888

Reconstructing Undersampled Non-Cartesian Data with Calibrationless Parallel Imaging

Daniel Neumann1, Felix A. Breuer1, Peter M. Jakob2, Gregory Lee3, Mark A. Griswold3, Nicole Seiberlich3

1Research Center Magnetic Resonance Bavaria (MRB), Wrzburg, Germany; 2Dept. of Experimental Physics 5, University of Wrzburg, Wrzburg, Germany; 3Dept. of Radiology, Case Western Reserve University, Cleveland, OH, United States

Non-Cartesian imaging has many known advantages over Cartesian imaging; however, complex parallel imaging techniques are required for such non-standard trajectories. In this work, we first use Calibrationless Parallel Imaging (CPI) to iteratively reconstruct fully-sampled and undersampled variable density spiral data. This method requires no explicit calibration data or coil sensitivity maps and offers robust reconstructions using in-vivo spiral data for acceleration factors up to 4. Our results suggest that CPI with GROG may overcome the problems of reconstructing images from accelerated non-Cartesian measurements using parallel imaging.