AIMC Topic: Radiography

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Deep learning for automated hip fracture detection and classification : achieving superior accuracy.

The bone & joint journal
AIMS: The aim of this study was to develop and evaluate a deep learning-based model for classification of hip fractures to enhance diagnostic accuracy.

Automated measurement of pelvic parameters using convolutional neural network in complex spinal deformities: overcoming challenges in coronal deformity cases.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Accurate and consistent measurement of sagittal alignment is challenging, particularly in patients with severe coronal deformities, including degenerative lumbar scoliosis (DLS).

Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis.

European radiology experimental
BACKGROUND: Minimizing radiation exposure is crucial in monitoring adolescent idiopathic scoliosis (AIS). Generative adversarial networks (GANs) have emerged as valuable tools being able to generate high-quality synthetic images. This study explores ...

A Deep Learning Tool for Minimum Joint Space Width Calculation on Antero-posterior Knee Radiographs.

The Journal of arthroplasty
BACKGROUND: Minimum joint space width (mJSW) is an important continuous quantitative metric of osteoarthritis progression in the knee. The purpose of this study was to develop an automated measurement algorithm for mJSW in the medial and lateral comp...

Development of a Deep Learning Model for Automating Implant Position in Total Hip Arthroplasty.

The Journal of arthroplasty
BACKGROUND: Novel methods for annotating antero-posterior pelvis radiographs and fluoroscopic images with deep-learning models have recently been developed. However, their clinical use has been limited. Therefore, the purpose of this study was to dev...

Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis.

Scientific reports
The Sharp-van der Heijde score (SvH) is crucial for assessing joint damage in rheumatoid arthritis (RA) through radiographic images. However, manual scoring is time-consuming and subject to variability. This study proposes a multistage deep learning ...

Automated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study.

La Radiologia medica
PURPOSE: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.

Stress radiography of medial knee instability provides a reliable correlation with the severity of injury and medial joint space opening-A robotic biomechanical cadaveric study.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: The medial collateral ligament (MCL), and posterior oblique ligament (POL) are the primary valgus stabilisers of the knee, and clinical examinations in grading valgus instability can be inherently subjective. Stress radiography of medial-sid...

Automatic skeletal maturity grading from pelvis radiographs by deep learning for adolescent idiopathic scoliosis.

Medical & biological engineering & computing
Adolescent idiopathic scoliosis (AIS) is a three-dimensional spine deformity governed of the spine. A child's Risser stage of skeletal maturity must be carefully considered for AIS evaluation and treatment. However, there are intra-observer and inter...

An open source convolutional neural network to detect and localize distal radius fractures on plain radiographs.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Distal radius fractures (DRFs) are often initially assessed by junior doctors under time constraints, with limited supervision, risking significant consequences if missed. Convolutional Neural Networks (CNNs) can aid in diagnosing fractures....