Developing fast accurate large-tip-angle radiofrequency pulses and gradient trajectories suitable for ‘online’ use is a challenging problem. In this work we propose a novel method for the sub-second design of RF pulses and gradient trajectories through use of a suitably trained artificial neural network which attempts to learn the required pulse and gradient spoke parameters from B1+ field spatial variations. A method for synthesising a large training database is also described. Our initial results highlight some of the challenges of this approach but suggest areas for future development.
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