AIMC Topic: Wrist Fractures

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Detecting pediatric wrist fractures using deep-learning-based object detection.

Pediatric radiology
BACKGROUND: Missed fractures are the leading cause of diagnostic error in the emergency department, and fractures of pediatric bones, particularly subtle wrist fractures, can be misidentified because of their varying characteristics and responses to ...

Detecting Distal Radius Fractures Using a Segmentation-Based Deep Learning Model.

Journal of digital imaging
Deep learning algorithms can be used to classify medical images. In distal radius fracture treatment, fracture detection and radiographic assessment of fracture displacement are critical steps. The aim of this study was to use pixel-level annotations...

Impact of test set composition on AI performance in pediatric wrist fracture detection in X-rays.

European radiology
OBJECTIVES: To evaluate how different test set sampling strategies-random selection and balanced sampling-affect the performance of artificial intelligence (AI) models in pediatric wrist fracture detection using radiographs, aiming to highlight the n...

Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images.

BMC musculoskeletal disorders
OBJECTIVE: The aim of this study was to develop a hybrid diagnostic framework integrating radiomic and deep features for accurate and reproducible detection and classification of wrist fractures using X-ray images.

Artificial intelligence-guided distal radius fracture detection on plain radiographs in comparison with human raters.

Journal of orthopaedic surgery and research
BACKGROUND: The aim of this study was to compare the performance of artificial intelligence (AI) in detecting distal radius fractures (DRFs) on plain radiographs with the performance of human raters.

[Study on automatic and rapid diagnosis of distal radius fracture by X-ray].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
This article aims to combine deep learning with image analysis technology and propose an effective classification method for distal radius fracture types. Firstly, an extended U-Net three-layer cascaded segmentation network was used to accurately seg...