PARTIALLY PARALLEL MR IMAGE RECONSTRUCTION USING SENSITIVITY ENCODING

A new algorithm is presented for efficiently solving image reconstruction problems that arise in partially parallel magnetic resonance imaging. This algorithm minimizes an objective function of the form phi(Bu) + 1/2 parallel to F(p)Su - f parallel to(2), where phi is the regularization term which may be nonsmooth. In image reconstruction, the phi term corresponds to total variation smoothing and/or L1 regularization term. The least square term 1/2 parallel to F(p)Su - f parallel to(2) is the fidelity term. In our application, f represents undersampled data from a partially parallel imaging (PPI) system. The proposed algorithm is a generalization of the Bregman operator splitting algorithm with variable stepsize (BOSVS) in which the previous Barzilai-Borwein (BB) step is replaced by a cyclic BB (CBB) step, and an L1 term psi is added to the energy function. Experimental results on clinical partially parallel imaging data are given.