Online dynamic magnetic resonance imaging based on pseudo-polar sampling and GPU acceleration

Abstract

Most of the online dynamic magnetic resonance imaging (dMRI) techniques are developed based on Cartesian trajectories. Recently, radial trajectories have been proposed to acquire image data for online dMRI. Compared with Cartesian trajectories, radial trajectories cover densely at k-space center and are more incoherent. When using compressed sensing technique to reconstruct dynamic images with under-sampling radial k-space data, the regridding procedure is employed, however it is usually time consuming and introduces numerical errors. In this study, a novel radial-like pseudo-polar (PP) trajectory was used for online dMRI. PP trajectory can avoid regridding and inverse-regridding operation by using a pseudopolar FFT (PPFFT) operation without interpolation. In the reconstructiongraphics processing unit (GPU) is used to further decrease the reconstruction time and achieve real-time online effect. In this simulation study, cardiac k-space dataset was fully acquired and using as a reference dataset. The PP trajectory was used to retrospectively under-sample k-space data with 12.5% and 25% coverage. The reconstruction results show that, the image quality of online dMRI based on PP under-sampling is higher than that of radial under-sampling based method. The reconstruction time was significantly shorten by using GPU acceleration, for the tested case, it is more than 20 times faster than the CPU computing.