AIMC Topic: Radiography
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A radiographic artificial intelligence tool to identify candidates suitable for partial knee arthroplasty.
Archives of orthopaedic and trauma surgery
Oct 3, 2024
INTRODUCTION: Knee osteoarthritis is a prevalent condition frequently necessitating knee replacement surgery, with demand projected to rise substantially. Partial knee arthroplasty (PKA) offers advantages over total knee arthroplasty (TKA), yet its u...
Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression.
Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Oct 1, 2024
Many models using the aid of artificial intelligence have been recently proposed to predict the progression of knee osteoarthritis. However, previous models have not been properly validated with an external data set or have reported poor predictive p...
Deep learning in Cobb angle automated measurement on X-rays: a systematic review and meta-analysis.
Spine deformity
Sep 25, 2024
PURPOSE: This study aims to provide an overview of different deep learning algorithms (DLAs), identify the limitations, and summarize potential solutions to improve the performance of DLAs.
High accuracy in lower limb alignment analysis using convolutional neural networks, with improvements needed for joint-level metrics.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Sep 22, 2024
PURPOSE: Evaluation of long-leg standing radiographs (LSR) is a standardised procedure for analysis of primary or secondary deformities of the lower limbs. Deep-learning convolutional neural networks (CNN) offer the potential to enhance radiological ...
Artificial intelligence and radiographer preliminary image evaluation: What might the future hold for radiographers providing x-ray interpretation in the acute setting?
Journal of medical radiation sciences
Sep 20, 2024
In a stretched healthcare system, radiographer preliminary image evaluation in the acute setting can be a means to optimise patient care by reducing error and increasing efficiencies in the patient journey. Radiographers have shown impressive accurac...
Quality control of elbow joint radiography using a YOLOv8-based artificial intelligence technology.
European radiology experimental
Sep 20, 2024
BACKGROUND: To explore an artificial intelligence (AI) technology employing YOLOv8 for quality control (QC) on elbow joint radiographs.
Hallux valgus and pes planus: Correlation analysis using deep learning-assisted radiographic angle measurements.
Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons
Sep 19, 2024
BACKGROUND: The relationship between hallux valgus (HV) and pes planus remains unresolved. This study aims to determine the correlation between HV and pes planus using a deep learning (DL) model to measure radiographic angle parameters.
An automated framework for pediatric hip surveillance and severity assessment using radiographs.
International journal of computer assisted radiology and surgery
Sep 16, 2024
PURPOSE: Hip dysplasia is the second most common orthopedic condition in children with cerebral palsy (CP) and may result in disability and pain. The migration percentage (MP) is a widely used metric in hip surveillance, calculated based on an anteri...
Deep Learning for Automated Classification of Hip Hardware on Radiographs.
Journal of imaging informatics in medicine
Sep 12, 2024
PURPOSE: To develop a deep learning model for automated classification of orthopedic hardware on pelvic and hip radiographs, which can be clinically implemented to decrease radiologist workload and improve consistency among radiology reports.
Artificial Intelligence-Based Surgery Support Model Using Intraoperative Radiographs for Assessing the Acetabular Component Angle.
The Journal of arthroplasty
Sep 12, 2024
BACKGROUND: This study aimed to develop an artificial intelligence-based surgical support model for assessing the acetabular component angle using intraoperative radiographs during total hip arthroplasty and verify its accuracy.
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