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Automated Age Estimation from OPG Images and Patient Records Using Deep Feature Extraction and Modified
Gulfem Ozlu Ucan1, Omar Abboosh Hussein Gwassi2, Burak Kerem Apaydin3
1Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Istanbul Gelisim University, Istanbul 34310, Turkey.
Diagnostics (Basel, Switzerland)
|February 13, 2025
Summary
Artificial intelligence (AI) offers a novel solution for dental age estimation from panoramic radiographs, overcoming manual measurement limitations. This AI system demonstrates high accuracy, paving the way for its use in forensic science.
Area of Science:
- Forensic Odontology
- Artificial Intelligence
- Radiographic Analysis
Background:
- Dental age estimation is crucial in forensic science for individual identification and age determination.
- Current methods face challenges due to methodological variability, biological differences, and time-consuming manual measurements.
- Automated age estimation from panoramic radiographs (OPGs) is needed to address these limitations.
Purpose of the Study:
- To develop and evaluate an artificial intelligence (AI) system for automatic tooth age estimation from panoramic radiographs (OPGs).
- To overcome the drawbacks of manual measurements, time consumption, and clinical application difficulties.
- To assess the efficacy of AI algorithms in enhancing the accuracy and efficiency of dental age estimation.
Main Methods:
- Utilized Two-Dimensional Deep Convolutional Neural Network (2D-DCNN) and One-Dimensional Deep Convolutional Neural Network (1D-DCNN) for feature extraction from OPGs and patient data.
- Employed a Modified Genetic-Random Forest Algorithm (MG-RF), combining Genetic Algorithm (GA) and Random Forest (RF) for age estimation.
- Analyzed system performance using Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared (R²) values.
Main Results:
- The AI system achieved highly accurate results with an MSE of 0.00027, MAE of 0.0079, RMSE of 0.0888, and an R² score of 0.999.
- The developed algorithms demonstrated exceptional performance in estimating tooth age from panoramic radiographs.
- The findings indicate a significant advancement in automated dental age estimation accuracy.
Conclusions:
- The AI-based system is a highly effective tool for dental age detection.
- This technology holds significant potential for future applications in forensic sciences.
- Automated age estimation from OPGs offers a reliable and efficient alternative to traditional methods.
