2 citations · 2 across the 3 of their papers we have counts for
4 papers
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.…
Ultra-fast (milliseconds), multi-dimensional RF pulse design with deep learning
Mads Sloth Vinding, Birk Skyum, Ryan Sangill +1
Purpose: Some advanced RF pulses, like multi-dimensional RF pulses, are often long and require substantial computation time due to a number of constraints and requirements, sometim…