Radiomics and machine learning–based methods offer exciting opportunities for improving
diagnostic performance and efficiency in musculoskeletal radiology for various tasks …

Simple Summary Magnetic Resonance Imaging (MRI) is a consolidated imaging tool for the
multiparametric assessment of tissues in various pathologies from degenerative and …

Background Detection of rotator cuff tears, a common cause of shoulder disability, can be
time-consuming and subject to reader variability. Deep learning (DL) has the potential to …

Objectives Automatic bone lesions detection and classifications present a critical challenge
and are essential to support radiologists in making an accurate diagnosis of bone lesions. In …

Osteoarthritis is a complex whole-organ disorder that involves molecular, anatomic, and
physiologic derangement. Advances in imaging techniques have expanded the role of …

Objective To evaluate if deep learning is a feasible approach for automated detection of
supraspinatus tears on MRI. Materials and methods A total of 200 shoulder MRI studies …

With the global outbreak of coronavirus disease 2019 (COVID-19), public health has
received unprecedented attention. The cultivation of emergency and compound …

Objectives The aim is to validate the performance of a deep convolutional neural network
(DCNN) for vertebral body measurements and insufficiency fracture detection on lumbar …

This narrative review focuses on clinical applications of artificial intelligence (AI) in
musculoskeletal imaging. A range of musculoskeletal disorders are discussed using a …

Foot and ankle injuries are common musculoskeletal disorders, broadly categorized as
traumatic and overuse injuries and chronic conditions. The ankle is the second most …