Skeletal age evaluation using hand X-rays to determine growth problems

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PeerJ Computer Science

Main article text

 

Introduction

  • To propose an approach that automatically recognizes characteristics in hand X-ray pictures and applies these characteristics to categorize skeletal bone age to identify growth disorders.

  • A simple customized CNN is employed to track the development of the hand’s bones in the bone age evaluation approach.

  • The proposed CNN model has shown superior performance when compared with the Visual Geometry Group (VGG) model.

  • Lowering the stress on X-ray diagnostic centers to lessen the burden on medical personnel in hospitals and health centers to deliver good services to patients.

Material and methods

Overview

Dataset description

Data preprocessing

Deep learning models

Evaluation parameters

Analysis of results

Results of customized CNN

Experimental results with VGG16

Comparison between customized CNN and VGG16

Comparison with state-of-the-art approaches from literature

Conclusion

Additional Information and Declarations

Competing Interests

Imran Ashraf is an Academic Editor for PeerJ Computer Science.

Author Contributions

Muhammad Umer conceived and designed the experiments, performed the experiments, analyzed the data, performed the computation work, authored or reviewed drafts of the article, and approved the final draft.

Ala’ Abdulmajid Eshmawi conceived and designed the experiments, analyzed the data, performed the computation work, authored or reviewed drafts of the article, and approved the final draft.

Khaled Alnowaiser performed the computation work, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Abdullah Mohamed conceived and designed the experiments, analyzed the data, performed the computation work, authored or reviewed drafts of the article, and approved the final draft.

Huda Alrashidi performed the experiments, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Imran Ashraf performed the experiments, prepared figures and/or tables, and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The data and code is available at GitHub and Zenodo:

https://github.com/MUmerSabir/PeerJBoneAge.

MUmerSabir. (2023). MUmerSabir/PeerJBoneAge: DOI Request (Main). Zenodo. https://doi.org/10.5281/zenodo.7792453.

Funding

The APC was supported via funding from the Prince Sattam bin Abdulaziz University project number (PSAU/2023/R/1445). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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