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Abstract #2636

Accelerated 3D Radial Imaging with 3D Variational Regularization

Florian Knoll1, Kai Tobias Block2, Kristian Bredies3, Clemens Diwoky1, Leon Axel4, Daniel K. Sodickson4, Rudolf Stollberger1

1Institute of Medical Engineering, Graz University of Technology, Graz, Styria, Austria; 2Center for Biomedical Imaging, NYU Langone Medical Center, New York, NY, United States; 3Department of Mathematics and Scientific Computing, University of Graz, Graz, Styria, Austria; 4Center for Biomedical Imaging, New York University School of Medicine, New York, NY, United States

Iterative parallel-imaging methods are highly promising for MR image reconstruction from undersampled data due to their flexibility to incorporate a priori knowledge using regularization. However, these methods are computationally very expensive and memory demanding. Consequently, most implementations so far used acquisition schemes that allow separating the reconstruction into smaller sub-problems, e.g. by reconstructing 3D volumes slice by slice. This comes at the expense of loosing acceleration capability in this direction, which limits the achievable overall scan efficiency. Furthermore, for certain imaging techniques like 3D radial ultra-short TE (UTE) imaging, separation of the reconstruction is not feasible. In this work, we present a method that treats the whole 3D imaging volume as single data set. This enables completely arbitrary 3D trajectories with acceleration in any dimension and incorporation of fully 3D regularization functionals.

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Keywords

accelerated acceleration achievable achieved acquisition adds afterwards aliasing arbitrary artifacts biomedical block brain capability channel channels clinical coil comes complete completely compressed computing conditioning constraint continuous described dimensions discs displayed distribution done dual efficiency enable enabled enables engineering expense expensive experimentally exploiting feasible finally flexibility full fully functionals furthermore future gain graphics hardware head highly human implementation implementations improve includes incoherence incoherent incoherently incorporating individual inherently initial invest isotropic iterative knoll knowledge limits linear magma mathematics matrix measured medicine mode modulation nearly novel object operator optimization overall parallel partition path patterns penalty phantom pock potential previously primal priori problem processing projections promising quality radial reconstructed reconstruction reconstructions reduce regularization removal residual respectively rotated running sampled sampling schemes school scientific sensing sensitivities separate separating slice solution space sphere spokes stack stacking stars still surface systems technically terms trajectories trajectory translates transversal treats ultra uniform unique variation variational verified virtual volume volunteer whole