An Effective Algorithm in Partial Fourier Parallel MRI Based on Robust Estimator

Partial Fourier acquisition and parallel imaging are two effective fast imaging techniques.Both techniques permit decreased acquisition times by reducing the amount of phased encoding needed.The benefits of the combined technique compared with the individual techniques are large reduced imaging time.Unfortunately,during the partial Fourier reconstruction processing,restoration of missing uncollected k-space data rely on corrupt Hermitian conjugate symmetry.This leads to minor phase variations and noise introduced,which in turn corrupt in SENSE process.In this paper,a constrained reconstruction algorithm is presented to remove artifact in images.We apply robust Annealing M(AM) Estimator scheme to suppress the corrupt data points and make solutions insensitive to the influence caused by outliers.Experimental results show that proposed method can effectively eliminate aliasing artifacts to enhance quality of reconstruction and imaging speed.