A variable projection approach to parallel magnetic resonance imaging

Accurate estimation of channel sensitivity functions is still a challenging problem in parallel imaging. JSENSE has recently been proposed to improve the accuracy of sensitivity estimation using the self calibration data. It regards both the coil sensitivities and the desired images as unknowns to be solved for jointly. The existing algorithm for the underlying nonlinear optimization problem requires an accurate initial value, which needs considerable number of self calibration data. In this paper, we use the variable projection method to find the optimal solution. The method is known to be able to give an optimal solution, and our implementation has a linear convergence rate. The performance of the proposed method is evaluated using a set of in vivo experiment data.