Rapid Sample Density Estimation for 3D Trajectories

Nicholas Ryan Zwart¹, James Grant Pipe¹

The reconstruction of non-cartesian k-space trajectories often requires the estimation of non-uniform sampling density. Particularly for 3D, this calculation can be computationally expensive. The method proposed in this work is the combination of a fast, previously proposed, iterative algorithm with a previously proposed optimized convolution kernel.