2 citations · 2 across the 4 of their papers we have counts for
4 papers
Accelerated Newton-Raphson GRAPE methods for optimal control
David L. Goodwin, Mads Sloth Vinding
A Hessian based optimal control method is presented in Liouville space to mitigate previously undesirable polynomial scaling of computation time. This new method, an improvement to…
Clipped DeepControl: deep neural network two-dimensional pulse design with an amplitude constraint layer
Mads Sloth Vinding, Torben Ellegaard Lund
Advanced radio-frequency pulse design used in magnetic resonance imaging has recently been demonstrated with deep learning of (convolutional) neural networks and reinforcement lear…
Optimal control gradient precision trade-offs: application to fast generation of DeepControl libraries for MRI
Mads Sloth Vinding, David L. Goodwin, Ilya Kuprov +1
We have recently demonstrated supervised deep learning methods for rapid generation of radiofrequency pulses in magnetic resonance imaging (https://doi.org/10.1002/mrm.27740, https…
DeepControl: 2D RF pulses facilitating inhomogeneity and off-resonance compensation in vivo at 7T
Mads Sloth Vinding, Christoph Stefan Aigner, Sebastian Schmitter +1
Purpose: Rapid 2D RF pulse design with subject specific inhomogeneity and off-resonance compensation at 7 T predicted from convolutional neural networks is presented.…