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Patellofemoral Joint

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[Improved technique for perforation of patella combined with suture anchor and non-tourniquet for repairing acute rupture of the bone tendon junction of quadriceps tendon].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery
OBJECTIVE: To investigate effectiveness of a improved technique for perforation of patella combined with suture anchor and non-tourniquet for repairing acute rupture of the bone tendon junction of quadriceps tendon.

Automated detection of patellofemoral osteoarthritis from knee lateral view radiographs using deep learning: data from the Multicenter Osteoarthritis Study (MOST).

Osteoarthritis and cartilage
OBJECTIVE: To assess the ability of imaging-based deep learning to detect radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs.

Automatic measurement of the patellofemoral joint parameters in the Laurin view: a deep learning-based approach.

European radiology
OBJECTIVES: To explore the performance of a deep learning-based algorithm for automatic patellofemoral joint (PFJ) parameter measurements from the Laurin view.

A More Posterior Tibial Tubercle (Decreased Sagittal Tibial Tubercle-Trochlear Groove Distance) Is Significantly Associated With Patellofemoral Joint Degenerative Cartilage Change: A Deep Learning Analysis.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To perform patellofemoral joint (PFJ) geometric measurements on knee magnetic resonance imaging scans and determine their relations with chondral lesions in a multicenter cohort using deep learning.

Knee landmarks detection via deep learning for automatic imaging evaluation of trochlear dysplasia and patellar height.

European radiology
OBJECTIVES: To develop and validate a deep learning-based approach to automatically measure the patellofemoral instability (PFI) indices related to patellar height and trochlear dysplasia in knee magnetic resonance imaging (MRI) scans.

Deep Learning for Predicting Progression of Patellofemoral Osteoarthritis Based on Lateral Knee Radiographs, Demographic Data, and Symptomatic Assessments.

Methods of information in medicine
OBJECTIVE: In this study, we propose a novel framework that utilizes deep learning and attention mechanisms to predict the radiographic progression of patellofemoral osteoarthritis (PFOA) over a period of 7 years.

Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability.

Scientific reports
This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. T...

Predicting Musculoskeletal Loading at Common Running Injury Locations Using Machine Learning and Instrumented Insoles.

Medicine and science in sports and exercise
INTRODUCTION: Wearables have the potential to provide accurate estimates of tissue loads at common running injury locations. Here we investigate the accuracy by which commercially available instrumented insoles (ARION; ATO-GEAR, Eindhoven, The Nether...

Application of a machine learning and optimization method to predict patellofemoral instability risk factors in children and adolescents.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Conservative treatment remains the standard approach for first-time patellar dislocations. While risk factors for patellofemoral instability, a common paediatric injury, are well-established in adults, data concerning the progression of paed...