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DeepControl: 2DRF pulses facilitating B 1 + inhomogeneity and B 0 off‐resonance compensation in vivo at 7 T
Author(s) -
Vinding Mads Sloth,
Aigner Christoph Stefan,
Schmitter Sebastian,
Lund Torben Ellegaard
Publication year - 2021
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.28667
Subject(s) - imaging phantom , convolutional neural network , pulse (music) , pulse sequence , convolution (computer science) , computer science , artificial neural network , compensation (psychology) , physics , nuclear magnetic resonance , artificial intelligence , algorithm , optics , materials science , pattern recognition (psychology) , psychology , psychoanalysis , detector
Purpose Rapid 2DRF pulse design with subject‐specific B 1 + inhomogeneity and B 0 off‐resonance compensation at 7 T predicted from convolutional neural networks is presented. Methods The convolution neural network was trained on half a million single‐channel transmit 2DRF pulses optimized with an optimal control method using artificial 2D targets, B 1 + and B 0 maps. Predicted pulses were tested in a phantom and in vivo at 7 T with measured B 1 + and B 0 maps from a high‐resolution gradient echo sequence. Results Pulse prediction by the trained convolutional neural network was done on the fly during the MR session in approximately 9 ms for multiple hand‐drawn regions of interest and the measured B 1 + and B 0 maps. Compensation of B 1 + inhomogeneity and B 0 off‐resonances has been confirmed in the phantom and in vivo experiments. The reconstructed image data agree well with the simulations using the acquired B 1 + and B 0 maps, and the 2DRF pulse predicted by the convolutional neural networks is as good as the conventional RF pulse obtained by optimal control. Conclusion The proposed convolutional neural network‐based 2DRF pulse design method predicts 2DRF pulses with an excellent excitation pattern and compensated B 1 + and B 0 variations at 7 T. The rapid 2DRF pulse prediction (9 ms) enables subject‐specific high‐quality 2DRF pulses without the need to run lengthy optimizations.