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A decoupled generative adversarial network for anterior cruciate ligament tear localization and quantification
The anterior cruciate ligament (ACL) is one of the most commonly injured ligaments in the knee. Accurate tear quantification of ACL plays a crucial...
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Anterior cruciate ligament tear detection based on convolutional neural network and generative adversarial neural network
Knee ligament tear injury is frequent in many volleyball, football, basketball, and cricket players. In the past, various deep learning-based ACL...
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A personalized insertion centers preoperative positioning method for minimally invasive surgery of cruciate ligament reconstruction
In the surgery of knee cruciate ligament repair, how to accurately and personalized obtain cruciate ligament insertion centers is the key issue and a...
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Diagnosing Knee Injuries from MRI with Transformer Based Deep Learning
Magnetic Resonance Images (MRI) examinations are widely used for diagnosing injuries in the knee. Automatic interpretable detection of meniscus,...
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Intelligent detection of knee injury in MRI exam
Knee injuries are one of the most common injuries that occur, especially among athletes and older people. They are broadly classified into three main...
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Detecting the presence of anterior cruciate ligament injury based on gait dynamics disparity and neural networks
The aim of this study is to develop a new pattern recognition-based method to model and discriminate gait dynamics disparity between anterior...
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Detecting the presence of anterior cruciate ligament deficiency based on a double pendulum model, intrinsic time-scale decomposition (ITD) and neural networks
The anterior cruciate ligament (ACL) possesses the function of stabilizing the knee joint through limiting anterior tibial translation and...
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Combining Mixed-Format Labels for AI-Based Pathology Detection Pipeline in a Large-Scale Knee MRI Study
Labeling for pathology detection is a laborious task, performed by highly trained and expensive experts. Datasets often have mixed formats, including...
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Design and evaluation of a wearable system to increase adherence to rehabilitation programmes in acute cruciate ligament (CL) rupture
Smart wearables for health monitoring, prevention, and patient support play a significant role in today’s treatment and home rehabilitation. The...
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Deep Convolutional Neural Network-Based Knee Injury Classification Using Magnetic Resonance Imaging
Radiologists tend to possess human error during pathologies scans for any abnormalities; thus, the introduction of automation shall has a great...
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SB-SSL: Slice-Based Self-supervised Transformers for Knee Abnormality Classification from MRI
The availability of large scale data with high quality ground truth labels is a challenge when develo** supervised machine learning solutions for...
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Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability
This work employs a pre-trained, multi-view Convolutional Neural Network (CNN) with a spatial attention block to optimise knee injury detection. An...
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Classification of Gait Patterns Using Kinematic and Kinetic Features, Gait Dynamics and Neural Networks in Patients with Unilateral Anterior Cruciate Ligament Deficiency
The anterior cruciate ligament (ACL) plays an important role in controlling knee joint stability. The literature provides conflicting information on...
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Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery
Reconstruction surgery of torn ligaments typically requires precise and anatomically correct fixation of the graft substitute on the bone surface....
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Adversarial Robustness of MR Image Reconstruction Under Realistic Perturbations
Deep Learning (DL) methods have shown promising results for solving ill-posed inverse problems such as MR image reconstruction from undersampled...
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Functional Effectiveness and User Experience Assessment of Knee Joint Protective Gear Fixation Methods During Physical Activity
With the increasing awareness of people’s protection during physical activities, the sports sector is gradually moving towards a more diverse and...
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A Machine Learning Model for Automation of Ligament Injury Detection Process
Good exploitation of medical data is very useful for patient assessment. It requires a diversity of skills and expertise since it concerns a large...
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Deep ensemble learning approach for lower limb movement recognition from multichannel sEMG signals
Walking is a complex task that requires consistent practice to master, and it involves the synchronisation between the lower limbs and the brain,...
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Application of artificial intelligence technology in the field of orthopedics: a narrative review
Artificial intelligence (AI) was a new interdiscipline of computer technology, mathematic, cybernetics and determinism. These years, AI had obtained...
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A Review on Smart Patient Monitoring and Management in Orthopaedics Using Machine Learning
Tremendous advances have occurred in the sphere of Artificial intelligence in the past years, particularly in the application of Machine learning....