An end-to-end-trainable iterative network architecture for accelerated radial multi-coil 2D cine MR image reconstruction.
Journal:
Medical physics
Published Date:
Apr 1, 2021
Abstract
PURPOSE: Iterative convolutional neural networks (CNNs) which resemble unrolled learned iterative schemes have shown to consistently deliver state-of-the-art results for image reconstruction problems across different imaging modalities. However, because these methods include the forward model in the architecture, their applicability is often restricted to either relatively small reconstruction problems or to problems with operators which are computationally cheap to compute. As a consequence, they have not been applied to dynamic non-Cartesian multi-coil reconstruction problems so far.
