A Projection-Based K-space Transformer Network for Undersampled Radial MRI Reconstruction with Limited Training Subjects. (arXiv:2206.07219v1 [eess.IV])

Web: http://arxiv.org/abs/2206.07219

The recent development of deep learning combined with compressed sensing
enables fast reconstruction of undersampled MR images and has achieved
state-of-the-art performance for Cartesian k-space trajectories. However,
non-Cartesian trajectories such as the radial trajectory need to be transformed
onto a Cartesian grid in each iteration of the network training, slowing down
the training process and posing inconvenience and delay during training.
Multiple iterations of nonuniform Fourier transform in the networks offset the
deep learning advantage of fast inference. Current approaches …

arxiv network projection space training transformer