GESPIRiT: ESPIRiT combined with GRAPPA while autocalibration data is insufficient

Parallel magnetic resonance imaging (pMRI) which utilizes the redundant information from different coil sensitivities has been widely used. As the number of coils increases, algorithms that reconstruct single combined image are more suitable for pMRI. Most single combined image reconstruction need explicit functions of coil sensitivity. As a result, estimation of the coil sensitivities is important in pMRI. Nowadays, ESPIRiT(Iterative self-consistent parallel imaging reconstruction using eigenvector maps) based on the estimation of coil sensitivities is an outstanding algorithm. However, ESPIRiT has its limitation, which estimates the coil sensitivities not very correctly, while the autocalibration data is insufficient. In this paper, we focus on the pMRI algorithms based on improving the estimation of coil sensitivities and propose a new algorithm called GESPIRiT (ESPIRiT combined with GRAPPA), which is based on combining ESPIRiT with GRAPPA to obtain better estimation of coil sensitivities and final reconstructed image. Experiments are applied to demonstrate its feasibility and efficiency.