Durga: A heuristically-optimized data collection strategy for volumetric magnetic resonance imaging

A heuristic design method for rapid volumetric magnetic resonance imaging data acquisition trajectories is presented, using a series of second-order cone optimization subproblems. Other researchers have considered non-raster data collection trajectories and under-sampled data patterns. This work demonstrates that much higher rates of under-sampling are possible with an asymmetric set of trajectories, with very little loss in resolution, but the addition of noise-like artefacts. The proposed data collection trajectory, Durga, further minimizes collection time by incorporating short un-refocused excitation pulses, resulting in above 98% collection efficiency for balanced steady state free precession imaging. The optimization subproblems are novel, in that they incorporate all requirements.