A Versatile Toolbox for Rapid, Joint Design of pTx RF and Gradient Pulses Using Pytorch's Autodifferentiation

Traditional pTx pulse design focuses on optimizing RF pulses with a fixed or parametrized gradient waveform. Utilizing fast GPUs for autodifferentiation, the optimization process becomes sufficiently efficient that RF pulses and the underlying gradient waveforms can be freely optimized concurrently within short time. This allows for the time-efficient creation of pTx pulses without prior knowledge about suitable gradient trajectories. Still, restrictions e.g. due to hardware limitations may be included into the optimization process. We provide a pulse design toolbox and demonstrate its ability to generate universal small-FA excitation pulses as well as large-FA pulses.