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Knee Joint

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Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND We aimed to develop and evaluate a deep learning-based method for fully automatic segmentation of knee joint MR imaging and quantitative computation of knee osteoarthritis (OA)-related imaging biomarkers. MATERIAL AND METHODS This retrospe...

Ensemble deep learning model for predicting anterior cruciate ligament tear from lateral knee radiograph.

Skeletal radiology
OBJECTIVE: To develop an ensemble deep learning model (DLM) predicting anterior cruciate ligament (ACL) tears from lateral knee radiographs and to evaluate its diagnostic performance.

Study on the correlation between early three-dimensional gait analysis and clinical efficacy after robot-assisted total knee arthroplasty.

Chinese journal of traumatology = Zhonghua chuang shang za zhi
PURPOSE: Robot-assisted technology is a forefront of surgical innovation that improves the accuracy of total knee arthroplasty (TKA). But whether the accuracy of surgery can improve the clinical efficacy still needs further research. The purpose of t...

Automated Detection Model Based on Deep Learning for Knee Joint Motion Injury due to Martial Arts.

Computational and mathematical methods in medicine
OBJECTIVE: Develop a set of knee joint martial arts injury monitoring models based on deep learning, train and evaluate the model's effectiveness.

Automatic segmentation model of intercondylar fossa based on deep learning: a novel and effective assessment method for the notch volume.

BMC musculoskeletal disorders
BACKGROUND: Notch volume is associated with anterior cruciate ligament (ACL) injury. Manual tracking of intercondylar notch on MR images is time-consuming and laborious. Deep learning has become a powerful tool for processing medical images. This stu...

Deep Learning-Based Multimodal 3 T MRI for the Diagnosis of Knee Osteoarthritis.

Computational and mathematical methods in medicine
The objective of this study was to investigate the application effect of deep learning model combined with different magnetic resonance imaging (MRI) sequences in the evaluation of cartilage injury of knee osteoarthritis (KOA). Specifically, an image...

Navigated and Robot-Assisted Technology in Total Knee Arthroplasty: Do Outcome Differences Achieve Minimal Clinically Important Difference?

The Journal of arthroplasty
BACKGROUND: In total knee arthroplasty (TKA), computer-assisted navigation (N-TKA) and robotic-assisted methods (RA-TKA) are intended to increase precision of mechanical and component alignment. However, the clinical significance of published patient...

Lower-Limb Joint Torque Prediction Using LSTM Neural Networks and Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Estimation of joint torque during movement provides important information in several settings, such as effect of athletes' training or of a medical intervention, or analysis of the remaining muscle strength in a wearer of an assistive device. The abi...

Improved-Mask R-CNN: Towards an accurate generic MSK MRI instance segmentation platform (data from the Osteoarthritis Initiative).

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
INTRODUCTION: Objective assessment of osteoarthritis (OA) Magnetic Resonance Imaging (MRI) scans can address the limitations of the current OA assessment approaches. Detecting and extracting bone, cartilage, and joint fluid is a necessary component f...