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Pediatric Radiology: An Analysis of AI-Powered Bone Age Determination Methods

Year: 2025

Type: article

Abstract: Significant progress has been made in using artificial intelligence, especially deep learning, to help doctors evaluate the bone age of children in medical images. Traditional methods like the Leather Tanner-Whitehouse and Greulich-Pyle approaches have some issues with consistency and accuracy. But with AI, there's been a big shift. This review looks at how AI has changed bone age evaluation over time, making it easier and more reliable. It covers different AI systems used, from older semi-automated ones like HANDX to newer ones like BoneXpert. The review explains how these systems work, their pros and cons, and how well they perform. It's a helpful guide for scientists, doctors, and anyone interested in this field, covering both old and new AI-driven methods for evaluating bone age.

Source: NTU Journal of Engineering and Technology

DOI: 10.56286/a82tjh48

Authors: Rayyan Mahmood Salih Alrawi, Nasseer M. Basheer

Institution: Northern Technical University

Language: English

Topic: Forensic Anthropology and Bioarchaeology Studies

Subfield: Archeology

Field: Arts and Humanities

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4408767833

FWCI: 8.303

Cites:

Cited by: 2

Related to: 10