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Knee Joint

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A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.

Osteoarthritis and cartilage
OBJECTIVE: This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance imaging (MRI) in characterizing structural tissue pathologies in osteoarthritis (OA) imaging research over the last 30 years.

Automated bone age assessment from knee joint by integrating deep learning and MRI-based radiomics.

International journal of legal medicine
Bone age assessment (BAA) is a crucial task in clinical, forensic, and athletic fields. Since traditional age estimation methods are suffered from potential radiation damage, this study aimed to develop and evaluate a deep learning radiomics method b...

Ensemble deep-learning networks for automated osteoarthritis grading in knee X-ray images.

Scientific reports
The Kellgren-Lawrence (KL) grading system is a scoring system for classifying the severity of knee osteoarthritis using X-ray images, and it is the standard X-ray-based grading system for diagnosing knee osteoarthritis. However, KL grading depends on...

Expanding from unilateral to bilateral: A robust deep learning-based approach for predicting radiographic osteoarthritis progression.

Osteoarthritis and cartilage
OBJECTIVE: To develop and validate a deep learning (DL) model for predicting osteoarthritis (OA) progression based on bilateral knee joint views.

Fully automated assessment of the knee alignment on long leg radiographs following corrective knee osteotomies in patients with valgus or varus deformities.

Archives of orthopaedic and trauma surgery
INTRODUCTION: The assessment of the knee alignment on long leg radiographs (LLR) postoperative to corrective knee osteotomies (CKOs) is highly dependent on the reader's expertise. Artificial Intelligence (AI) algorithms may help automate and standard...

Mixed Reality and Artificial Intelligence: A Holistic Approach to Multimodal Visualization and Extended Interaction in Knee Osteotomy.

IEEE journal of translational engineering in health and medicine
OBJECTIVE: Recent advancements in augmented reality led to planning and navigation systems for orthopedic surgery. However little is known about mixed reality (MR) in orthopedics. Furthermore, artificial intelligence (AI) has the potential to boost t...

Deep learning generated lower extremity radiographic measurements are adequate for quick assessment of knee angular alignment and leg length determination.

Skeletal radiology
PURPOSE: Angular and longitudinal deformities of leg alignment create excessive stresses across joints, leading to pain and impaired function. Multiple measurements are used to assess these deformities on anteroposterior (AP) full-length radiographs....

Efficacy of the newly designed "SkyWalker" robot compared to the MAKO robotic system in primary total knee arthroplasty: a one-year follow-up study.

International orthopaedics
PURPOSE: Robot-assisted surgical systems for performing total knee arthroplasty (TKA) have gained significant attention. This study was designed to compare the surgical outcomes in primary TKA surgery between the recently developed "SkyWalker" robot ...

Simplifying radiologic reports with natural language processing: a novel approach using ChatGPT in enhancing patient understanding of MRI results.

Archives of orthopaedic and trauma surgery
PURPOSE: The aim of this prospective cohort study was to assess the factual accuracy, completeness of medical information, and potential harmfulness of incorrect conclusions by medical professionals in automatically generated texts of varying complex...

Estimation of Lower Limb Joint Angles and Joint Moments during Different Locomotive Activities Using the Inertial Measurement Units and a Hybrid Deep Learning Model.

Sensors (Basel, Switzerland)
Using inertial measurement units (IMUs) to estimate lower limb joint kinematics and kinetics can provide valuable information for disease diagnosis and rehabilitation assessment. To estimate gait parameters using IMUs, model-based filtering approache...