Purpose: To retrospectively compare the diagnostic performance of 1.5- and 3.0-T magnetic
resonance (MR) imaging protocols for evaluating the articular cartilage of the knee joint in …

Purpose To describe and evaluate a new fully automated musculoskeletal tissue segmentation
method using deep convolutional neural network (CNN) and three‐dimensional (3D) …

Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic
resonance (MR) imaging–based attenuation correction (AC) (termed deep MRAC) in brain …

Purpose To determine whether a three-dimensional isotropic resolution fast spin-echo sequence
(FSE-Cube) has similar diagnostic performance as a routine magnetic resonance (MR) …

Purpose To determine the feasibility of using a deep learning approach to detect cartilage
lesions (including cartilage softening, fibrillation, fissuring, focal defects, diffuse thinning due to …

Purpose: To retrospectively compare the sensitivity and specificity of previously described
magnetic resonance (MR) imaging criteria for the detection of instability in patients with …

Purpose To determine whether the addition of a T2 mapping sequence to a routine magnetic
resonance (MR) imaging protocol could improve diagnostic performance in the detection of …

Purpose To describe and evaluate a new segmentation method using deep convolutional
neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex …

OBJECTIVE. The purpose of this study was to use the Kellgren-Lawrence, Ahlback, and Brandt
grading scales to correlate radiographic grade of osteoarthritis with the actual degree of …

OBJECTIVE. The purpose of our study was to determine whether tears of the posterior root of
the lateral meniscus can be diagnosed using standard MR criteria of a meniscal tear in the …