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Abstract #2721

Improved Reconstruction in Non-Cartesian Parallel Imaging by Regularized Nonlinear Inversion

Florian Knoll1, Christian Clason2, Martin Uecker3, Rudolf Stollberger1

1Institute of Medical Engineering, TU Graz, Graz, Austria; 2Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria; 3Biomedizinische NMR Forschungs GmbH, MPI fr biophysikalische Chemie, Goettingen, Germany

It has been shown recently that it is possible to reformulate image reconstruction for Cartesian autocalibrated parallel imaging as a non-linear inversion problem. This approach allows joint optimization of the estimated coil sensitivities and image content, which improves image quality. We extend this method to arbitrary non-Cartesian sampling patterns. This eliminates the need to collect additional reference lines for the estimation of the coil sensitivities, and enables the use of even higher acceleration factors. Excellent removal of undersampling artifacts was achieved for human brain images (matrix size: 256x256, 32 radial projections, 4 channel head coil).