Abstract: A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a B0 magnet configured to provide a B0 field for the MRI system; gradient coils configured to provide gradient fields for the MRI system; and at least one RF coil configured to detect magnetic resonance (MR) signals; and a controller configured to: control the magnetics system to acquire MR spatial frequency data using non-Cartesian sampling; and generate an MR image from the acquired MR spatial frequency data using a neural network model comprising one or more neural network blocks including a first neural network block, wherein the first neural network block is configured to perform data consistency processing using a non-uniform Fourier transformation.

Abstract: Generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system by: generating first and second sets of one or more MR images from first and second input MR data; aligning the first and second sets of MR images using a neural network model comprising first and second neural networks, the aligning comprising: estimating, using the first neural network, a first transformation between the first and second sets of MR images; generating a first updated set of MR images from the second set of MR images using the first transformation; estimating, using the second neural network, a second transformation between the first set and the first updated set of MR images; and aligning the first set of MR images and the second set of MR images at least in part by using the first transformation and the second transformation.