Magnetic Resonance Imaging (MRI) of the musculoskeletal system is one of the most
common examinations in clinical routine. The application of Deep Learning (DL) …

Purpose To evaluate two settings (noise reduction of 50% or 75%) of a deep learning (DL)
reconstruction model relative to each other and to conventional MR image reconstructions …

Background Deep learning (DL)–based MRI reconstructions can reduce examination times
for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based …

Objectives The aim of this study was to evaluate the image quality and diagnostic
performance of a deep-learning (DL)–accelerated two–dimensional (2D) turbo spin echo …

Deep Learning Reconstruction The most recent advances in accelerating musculoskeletal
MRI use deep learning reconstruction (DLR) techniques. These advances have been …

Background Several deep learning-based methods have been proposed for addressing the
long scanning time of magnetic resonance imaging. Most are trained using brain 3T …

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

Objectives To compare interobserver agreement and image quality of 3D T2-weighted fast
spin echo (T2w-FSE) L-spine MRI images processed with a deep learning reconstruction …

Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …

Objective The study aims to evaluate the diagnostic performance of deep learning–based
reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and …