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Abstract #0202

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

Dario Bosch1,2, Jonas Bause1, and Klaus Scheffler1,2
1High Field MR Center, MPI for Biological Cybernetics, Tuebingen, Germany, 2Department for Biomedical Magnetic Resonance, University Hospital Tübingen, Tuebingen, Germany

Synopsis

Keywords: Parallel Transmit & Multiband, RF Pulse Design & Fields, Python, PyTorch, OptimizationTraditional 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.

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Keywords