Parallel Imaging using a Non-Uniform Undersampling Trajectory

Yu Li¹, Charles L. Dumoulin¹

This work introduces a novel parallel imaging technique that uses a non-uniform k-space undersampling trajectory to accelerate Cartesian data acquisition for MRI. In this technique, a non-uniform undersampling trajectory is formed from multiple uniform sub-trajectories with higher undersampling factors. A modulation model is used to separate non-uniformly undersampled data into aliasing and real image data in k-space. A set of linear filters is used to pass real image and block aliasing for reconstruction. In high-resolution brain imaging, it is demonstrated that a non-uniform trajectory gives better performance in parallel imaging with high acceleration factors than a uniform trajectory.