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Knee Injuries

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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.

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...

Comparison of Robot-Assisted Percutaneous Cannulated Screws Versus Open Reduction and Internal Fixation in Calcaneal Fractures.

Orthopaedic surgery
OBJECTIVE: Accurate placement of the screws is challenging in percutaneous cannulated screw fixation of calcaneal fractures, and robot-assisted (RA) surgery enhances the accuracy. We investigated the outcome of percutaneous cannulated screw fixation ...

Feasibility of AI-assisted compressed sensing protocols in knee MR imaging: a prospective multi-reader study.

European radiology
OBJECTIVES: To evaluate the image quality and diagnostic performance of AI-assisted compressed sensing (ACS) accelerated two-dimensional fast spin-echo MRI compared with standard parallel imaging (PI) in clinical 3.0T rapid knee scans.

Artificial intelligence for detection of effusion and lipo-hemarthrosis in X-rays and CT of the knee.

European journal of radiology
BACKGROUND: Traumatic knee injuries are challenging to diagnose accurately through radiography and to a lesser extent, through CT, with fractures sometimes overlooked. Ancillary signs like joint effusion or lipo-hemarthrosis are indicative of fractur...

Deep Learning Reconstructed New-Generation 0.55 T MRI of the Knee-A Prospective Comparison With Conventional 3 T MRI.

Investigative radiology
OBJECTIVES: The aim of this study was to compare deep learning reconstructed (DLR) 0.55 T magnetic resonance imaging (MRI) quality, identification, and grading of structural anomalies and reader confidence levels with conventional 3 T knee MRI in pat...

Deep Learning Superresolution for Simultaneous Multislice Parallel Imaging-Accelerated Knee MRI Using Arthroscopy Validation.

Radiology
Background Deep learning (DL) methods can improve accelerated MRI but require validation against an independent reference standard to ensure robustness and accuracy. Purpose To validate the diagnostic performance of twofold-simultaneous-multislice (S...

A Robotic Clamped-Kinematic System to Study Knee Ligament Injury.

Annals of biomedical engineering
Knee ligament injury is among the most common sports injuries and is associated with long recovery periods and low return-to-sport rates. Unfortunately, the mechanics of ligament injury are difficult to study in vivo, and computational studies provid...

MRI deep learning models for assisted diagnosis of knee pathologies: a systematic review.

European radiology
OBJECTIVES: Despite showing encouraging outcomes, the precision of deep learning (DL) models using different convolutional neural networks (CNNs) for diagnosis remains under investigation. This systematic review aims to summarise the status of DL MRI...