AIMC Topic: Hand Bones

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Automated Bone Age Assessment and Adult Height Prediction from Pediatric Hand Radiographs via a Cascaded Deep Learning Framework.

Journal of medical systems
Bone age assessment and adult height prediction are essential for evaluating pediatric growth. Traditional methods rely on manual radiographic interpretation, which is subjective, time-consuming, and prone to inter-observer variability. This study pr...

Determination of Skeletal Age From Hand Radiographs Using Deep Learning.

The American journal of sports medicine
BACKGROUND: Surgeons treating skeletally immature patients use skeletal age to determine appropriate surgical strategies. Traditional bone age estimation methods utilizing hand radiographs are time-consuming.

Generating accurate sex estimation from hand X-ray images using AI deep-learning techniques: A study of limited bone regions.

Legal medicine (Tokyo, Japan)
Hand bone structure provides valuable features for sex estimation. This research introduces a novel approach using Artificial Intelligence (AI), specifically Convolutional Neural Networks (CNNs), to classify sex from hand X-ray images, focusing on th...

Automatic bone age assessment: a Turkish population study.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: Established methods for bone age assessment (BAA), such as the Greulich and Pyle atlas, suffer from variability due to population differences and observer discrepancies. Although automated BAA offers speed and consistency, limited research e...

A critical comparative study of the performance of three AI-assisted programs for bone age determination.

European radiology
OBJECTIVES: To date, AI-supported programs for bone age (BA) determination for medical use in Europe have almost only been validated separately, according to Greulich and Pyle (G&P). Therefore, the current study aimed to compare the performance of th...

Deep learning-based automated bone age estimation for Saudi patients on hand radiograph images: a retrospective study.

BMC medical imaging
PURPOSE: In pediatric medicine, precise estimation of bone age is essential for skeletal maturity evaluation, growth disorder diagnosis, and therapeutic intervention planning. Conventional techniques for determining bone age depend on radiologists' s...

Adaptive Multi-Dimensional Weighted Network With Category-Aware Contrastive Learning for Fine-Grained Hand Bone Segmentation.

IEEE journal of biomedical and health informatics
Accurately delineating and categorizing individual hand bones in 3D ultrasound (US) is a promising technology for precise digital diagnostic analysis. However, this is a challenging task due to the inherent imaging limitations of the US and the insig...

Applicability and robustness of an artificial intelligence-based assessment for Greulich and Pyle bone age in a German cohort.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
PURPOSE: The determination of bone age (BA) based on the hand and wrist, using the 70-year-old Greulich and Pyle (G&P) atlas, remains a widely employed practice in various institutions today. However, a more recent approach utilizing artificial intel...

External validation of deep learning-based bone-age software: a preliminary study with real world data.

Scientific reports
Artificial intelligence (AI) is increasingly being used in bone-age (BA) assessment due to its complicated and lengthy nature. We aimed to evaluate the clinical performance of a commercially available deep learning (DL)-based software for BA assessme...

Probing an AI regression model for hand bone age determination using gradient-based saliency mapping.

Scientific reports
Understanding how a neural network makes decisions holds significant value for users. For this reason, gradient-based saliency mapping was tested on an artificial intelligence (AI) regression model for determining hand bone age from X-ray radiographs...