This article provides a focused overview of emerging technology in musculoskeletal MRI
and CT. These technological advances have primarily focused on decreasing examination …

Magnetic resonance imaging (MRI) is the keystone of modern musculoskeletal imaging;
however, long pulse sequence acquisition times may restrict patient tolerability and access …

Deep learning (DL) has had unprecedented success and is now entering scientific
computing with full force. However, current DL methods typically suffer from instability, even …

Accelerating MRI scans is one of the principal outstanding problems in the MRI research
community. Towards this goal, we hosted the second fastMRI competition targeted towards …

Background MRI is a powerful diagnostic tool with a long acquisition time. Recently, deep
learning (DL) methods have provided accelerated high-quality image reconstructions from …

In the past five years, deep learning methods have become state-of-the-art in solving various
inverse problems. Before such approaches can find application in safety-critical fields, a …

In recent years, there has been an intensive development of portable ultralow-field magnetic
resonance imaging (MRI) for low-cost, shielding-free, and point-of-care applications …

Convolutional Neural Networks (CNNs) are highly effective for image reconstruction
problems. Typically, CNNs are trained on large amounts of training images. Recently …

Deep neural networks give state-of-the-art accuracy for reconstructing images from few and
noisy measurements, a problem arising for example in accelerated magnetic resonance …

Purpose To systematically investigate the influence of various data consistency layers and
regularization networks with respect to variations in the training and test data domain, for …