Deep, Deep Learning with BART. (arXiv:2202.14005v2 [cs.CV] UPDATED)

Purpose: To develop a deep-learning-based image reconstruction framework for
reproducible research in MRI.

Methods: The BART toolbox offers a rich set of implementations of calibration
and reconstruction algorithms for parallel imaging and compressed sensing. In
this work, BART was extended by a non-linear operator framework that provides
automatic differentiation to allow computation of gradients. Existing
MRI-specific operators of BART, such as the non-uniform fast Fourier transform,
are directly integrated into this framework and are complemented by common
building blocks used …

arxiv bart deep learning