Iterative GRAPPA (iGRAPPA) for improved parallel imaging reconstruction

Abstract

In this work an iterative reconstruction method based on generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstruction is introduced. In the new method the reconstructed lines are used to reestimate and refine the weights from all the acquired data by applying the GRAPPA procedure iteratively with regularization. Both phantom and in vivo MRI experiments demonstrated that, compared to GRAPPA, the iterative approach reduces parallel imaging artifacts and permits high-quality image reconstruction with a relatively small number of calibration lines and slight changes of GRAPPA weights. © 2008 Wiley-Liss, Inc.