An unrolled split Bregman network with two learned convolutional regularizers reconstructs parallel MRI from undersampled k-space without explicit coil sensitivity estimation.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.IV 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging
An unrolled split Bregman network with two learned convolutional regularizers reconstructs parallel MRI from undersampled k-space without explicit coil sensitivity estimation.