Objective Magnetic resonance imaging (MRI) is gradually replacing computed tomography
(CT) in the examination of bones and joints. The accurate and automatic segmentation of the …

Background Magnetic resonance imaging (MRI) has been known to replace computed
tomography (CT) for bone and skeletal joint examination. The accurate automatic …

Magnetic resonance imaging (MRI) is now commonly used for the examination and
diagnosis of joints. A key step is to segment the bones of interest in MRI. This paper presents …

Three-dimensional (3D)-image-based anatomical analysis of rotator cuff tear patients has
been proposed as a way to improve repair prognosis analysis to reduce the incidence of …

For diagnosis of shoulder illness, it is essential to look at the morphology deviation of
scapula and humerus from the medical images that are acquired from Magnetic Resonance …

Mask Region-Based Convolutional Neural Network segmentation of the humerus and scapula
from proton density-weighted axial shoulder magnetic resonance images - PMC Back to Top …

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

Automatic segmentation of knee bone structures is an important task in orthopedics
diagnosis of knee disease based on MRI images. Inspired by doctors' diagnosis of knee in …

Three-dimensional (3D) images are widely used in the medical field (eg, CT, MRI). In
osteoarthritis research, 3D magnetic resonance imaging (MRI) provides a noninvasive way …

In medical image segmentation, the neural network structure of the U‐Net family has
demonstrated sufficient advantages. However, MRI images have different scan parameters …