AIMC Topic: Arthroscopy
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Deep Learning for US Image Quality Assessment Based on Femoral Cartilage Boundary Detection in Autonomous Knee Arthroscopy.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
Knee arthroscopy is a complex minimally invasive surgery that can cause unintended injuries to femoral cartilage or postoperative complications, or both. Autonomous robotic systems using real-time volumetric ultrasound (US) imaging guidance hold pote...
Radiographic Indices Are Not Predictive of Clinical Outcomes Among 1735 Patients Indicated for Hip Arthroscopic Surgery: A Machine Learning Analysis.
The American journal of sports medicine
Sep 14, 2020
BACKGROUND: The relationship between the preoperative radiographic indices for femoroacetabular impingement syndrome (FAIS) and postoperative patient-reported outcome measure (PROM) scores continues to be under investigation, with inconsistent findin...
Deep Learning Approach for Anterior Cruciate Ligament Lesion Detection: Evaluation of Diagnostic Performance Using Arthroscopy as the Reference Standard.
Journal of magnetic resonance imaging : JMRI
Jul 26, 2020
BACKGROUND: MRI is the most commonly used imaging method for diagnosing anterior cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time-intensive and depends on the clinical experience of the reader. An automated detection ...
Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference.
Skeletal radiology
Mar 13, 2020
OBJECTIVE: To clinically validate a fully automated deep convolutional neural network (DCNN) for detection of surgically proven meniscus tears.
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...
Application of Machine Learning for Predicting Clinically Meaningful Outcome After Arthroscopic Femoroacetabular Impingement Surgery.
The American journal of sports medicine
Dec 23, 2019
BACKGROUND: Hip arthroscopy has become an important tool for surgical treatment of intra-articular hip pathology. Predictive models for clinically meaningful outcomes in patients undergoing hip arthroscopy for femoroacetabular impingement syndrome (F...
Deep Learning-Based Femoral Cartilage Automatic Segmentation in Ultrasound Imaging for Guidance in Robotic Knee Arthroscopy.
Ultrasound in medicine & biology
Nov 22, 2019
Knee arthroscopy is a minimally invasive surgery used in the treatment of intra-articular knee pathology which may cause unintended damage to femoral cartilage. An ultrasound (US)-guided autonomous robotic platform for knee arthroscopy can be envisio...
A randomized comparison between interscalene and combined infraclavicular-suprascapular blocks for arthroscopic shoulder surgery.
Canadian journal of anaesthesia = Journal canadien d'anesthesie
Dec 19, 2017
BACKGROUND: This randomized trial aimed to evaluate combined infraclavicular-suprascapular blocks (ICB-SSBs) as a diaphragm-sparing alternative to interscalene blocks (ISBs) for arthroscopic shoulder surgery. We hypothesized that ICB-SSB would provid...
[The standardization and digitalization and intelligentization represent the future development direction of hip arthroscopy diagnosis and treatment technology].
Zhonghua yi xue za zhi
Jul 8, 2025
In recent years, hip arthroscopy has made great progress and has been extended to the treatment of intra-articular or periarticular diseases. However, the complex structure of the hip joint, high technical operation requirements and relatively long l...
Concomitant Procedures, Black Race, Male Sex, and General Anesthesia Show Fair Predictive Value for Prolonged Rotator Cuff Repair Operative Time: Analysis of the National Quality Improvement Program Database Using Machine Learning.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
May 1, 2025
PURPOSE: To develop machine learning models using the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database to predict prolonged operative time (POT) for rotator cuff repair (RCR), as well as use the trained machine l...
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