We investigate a method for the design of radio frequency (RF) pulses for custom simultaneous multi slice spatial profiles. We trained a variation of residual neural networks on a dataset of 96,000 generated adiabatic “power independent of the number of slices” (PINS) RF pulses, varying parameters such as gradient duty cycle, number of pulse lobes, quadratic phase strength, and transition and filter bandwidth. We compared the direct-design RF pulses to those generated by our model.
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