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Abstract #4627

3D Selective RF and Gradient Waveforms designed by using a GPU Accelerated Genetic Algorithm

Christopher Mirfin1, Paul Glover1, and Richard Bowtell1

1Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, United Kingdom

The Genetic Algorithm (GA) is motivated by the process of natural selection, allowing mutliple initialisations. Due to the stochastic nature of genetic algorithms they are beneficial in avoiding local minima, although they can require significantly more function evaluations to run than a traditional solver. In this work, motivated by the field of shape optimisation, an approach is taken to perform the joint design of RF and gradient waveforms using a GA with a GPU-accelerated iterative solver.

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