Osteoarthritis (OA) is one of the major health issues among the elderly population. MRI is the
most popular technology to observe and evaluate the progress of OA course. However, the …

Using magnetic resonance imaging (MRI) in osteoarthritis pathogenesis research has
proven extremely beneficial. However, it is always challenging for both clinicians and …

Magnetic resonance imaging (MRI) is precise and efficient for interpreting the soft and hard
tissues. Moreover, for the detailed diagnosis of varied diseases such as knee rheumatoid …

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

Knee Osteoarthritis (KOA) is the third most prevalent Musculoskeletal Disorder (MSD) after
neck and back pain. To monitor such a severe MSD, a segmentation map of the femur, tibia …

Magnetic resonance imaging (MRI) has proved to be an invaluable component of
pathogenesis research in osteoarthritis. Nevertheless, the detection of a meniscal lesion …

In this paper, we present an evaluation framework for the 3D segmentation of knee bones
and cartilage from magnetic resonance images. The framework was established for one of …

The segmentation of knee joint is of great significance for diagnosis, guidance and treatment
of knee osteoarthritis. However, manual delineation is time-consuming and labor-intensive …

Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from
Magnetic Resonance (MR) Images Using a Deep Learning Model - PMC Back to Top Skip to …

Segmentation of medical images into different tissue types is essential for many
advancements in orthopaedic research; however, manual segmentation techniques can be …