[HTML][HTML] Fully automatic knee joint segmentation and quantitative analysis for osteoarthritis from magnetic resonance (MR) images using a deep learning model
X Tang, D Guo, A Liu, D Wu, J Liu, N Xu… - Medical Science Monitor …, 2022 - ncbi.nlm.nih.gov
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 …
Magnetic Resonance (MR) Images Using a Deep Learning Model - PMC Back to Top Skip to …
From classical to deep learning: review on cartilage and bone segmentation techniques in knee osteoarthritis research
Knee osteoarthritis is a major diarthrodial joint disorder with profound global socioeconomic
impact. Diagnostic imaging using magnetic resonance image can produce morphometric …
impact. Diagnostic imaging using magnetic resonance image can produce morphometric …
Magnetic resonance imaging assessments for knee segmentation and their use in combination with machine/deep learning as predictors of early osteoarthritis …
J Martel-Pelletier, P Paiement… - Therapeutic Advances …, 2023 - journals.sagepub.com
Knee osteoarthritis (OA) is a prevalent and disabling disease that can develop over
decades. This disease is heterogeneous and involves structural changes in the whole joint …
decades. This disease is heterogeneous and involves structural changes in the whole joint …
Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging
Purpose To describe and evaluate a new fully automated musculoskeletal tissue
segmentation method using deep convolutional neural network (CNN) and three …
segmentation method using deep convolutional neural network (CNN) and three …
A coarse-to-fine framework for automated knee bone and cartilage segmentation data from the osteoarthritis initiative
Knee osteoarthritis (OA) is a degenerative joint disease that is prevalent in advancing age.
The pathology of OA disease is still unclear, and there are no effective interventions that can …
The pathology of OA disease is still unclear, and there are no effective interventions that can …
Deep learning‐based segmentation of knee MRI for fully automatic subregional morphological assessment of cartilage tissues: Data from the Osteoarthritis Initiative
Morphological changes in knee cartilage subregions are valuable imaging‐based
biomarkers for understanding progression of osteoarthritis, and they are typically detected …
biomarkers for understanding progression of osteoarthritis, and they are typically detected …
Automated tibiofemoral joint segmentation based on deeply supervised 2D-3D ensemble U-Net: Data from the Osteoarthritis Initiative
MH Abd Latif, I Faye - Artificial intelligence in medicine, 2021 - Elsevier
Improving longevity is one of the greatest achievements in humanity. Because of this, the
population is growing older, and the ubiquity of knee osteoarthritis (OA) is on the rise …
population is growing older, and the ubiquity of knee osteoarthritis (OA) is on the rise …
Automated segmentation of knee articular cartilage: Joint deep and hand-crafted learning-based framework using diffeomorphic mapping
Segmentation of knee articular cartilage tissue (ACT) from 3D magnetic resonance images
(MRIs) is a fundamental task in assessing knee osteoarthritis (KOA). However, automated …
(MRIs) is a fundamental task in assessing knee osteoarthritis (KOA). However, automated …
Computer-aided knee joint magnetic resonance image segmentation-a survey
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 …
most popular technology to observe and evaluate the progress of OA course. However, the …
Deep convolutional neural network for segmentation of knee joint anatomy
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 …
neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex …