AIMC Topic: Knee Joint
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The Impact of ACL Laxity on a Bicondylar Robotic Knee and Implications in Human Joint Biomechanics.
IEEE transactions on bio-medical engineering
Feb 5, 2020
OBJECTIVE: Elucidating the role of structural mechanisms in the knee can improve joint surgeries, rehabilitation, and understanding of biped locomotion. Identification of key features, however, is challenging due to limitations in simulation and in-v...
The Use of Artificial Intelligence in the Evaluation of Knee Pathology.
Seminars in musculoskeletal radiology
Jan 28, 2020
Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic ev...
Preliminary experience with an image-free handheld robot for total knee arthroplasty: 77 cases compared with a matched control group.
European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
Jan 16, 2020
BACKGROUND: Achieving an optimal limb alignment is an important factor affecting the long-term survival of total knee arthroplasty (TKA). This is the first study to look at the limb alignment and orientation of components in TKA using a novel image-f...
Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
Computer methods and programs in biomedicine
Jan 11, 2020
BACKGROUND AND OBJECTIVE: Segmentation is a crucial step in multiple biomechanics and orthopedics applications. The time-intensiveness and expertise requirements of medical image segmentation present a significant bottleneck for corresponding workflo...
Automated detection & classification of knee arthroplasty using deep learning.
The Knee
Dec 26, 2019
BACKGROUND: Preoperative identification of knee arthroplasty is important for planning revision surgery. However, up to 10% of implants are not identified prior to surgery. The purposes of this study were to develop and test the performance of a deep...
Siam-U-Net: encoder-decoder siamese network for knee cartilage tracking in ultrasound images.
Medical image analysis
Dec 23, 2019
The tracking of the knee femoral condyle cartilage during ultrasound-guided minimally invasive procedures is important to avoid damaging this structure during such interventions. In this study, we propose a new deep learning method to track, accurate...
Lower Body Kinematics Monitoring in Running Using Fabric-Based Wearable Sensors and Deep Convolutional Neural Networks.
Sensors (Basel, Switzerland)
Dec 3, 2019
Continuous kinematic monitoring of runners is crucial to inform runners of inappropriate running habits. Motion capture systems are the gold standard for gait analysis, but they are spatially limited to laboratories. Recently, wearable sensors have g...
The Effect of Optic Flow Speed on Active Participation During Robot-Assisted Treadmill Walking in Healthy Adults.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Nov 25, 2019
This study aimed to investigate: 1) the effect of optic flow speed manipulation on active participation during robot-assisted treadmill walking (RATW), 2) the influence of the type of virtual environment, and 3) the level of motion sickness and enjoy...
MR Protocol Optimization With Deep Learning: A Proof of Concept.
Current problems in diagnostic radiology
Oct 21, 2019
PURPOSE: This study was performed to demonstrate that a properly trained convolutional neural net (CNN) can provide an acceptable surrogate for human readers when performing a protocol optimization study. Tears of the anterior cruciate ligament (ACL)...
Effect of surgical parameters on the biomechanical behaviour of bicondylar total knee endoprostheses - A robot-assisted test method based on a musculoskeletal model.
Scientific reports
Oct 10, 2019
The complicated interplay of total knee replacement (TKR) positioning and patient-specific soft tissue conditions still causes a considerable number of unsatisfactory outcomes. Therefore, we deployed a robot-assisted test method, in which a six-axis ...
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