Chronological Age Detection Using Dental Panoramic Images

DOI

10.2991/978-94-6463-858-5_47How to use a DOI?

Keywords

YOLOv11; deep learning; chronological age detection; dental panoramic X-ray; non-invasive estimation; forensic science; preprocessing techniques; model accuracy; transfer learning; multimodal approaches

Abstract

This study investigates the YOLOv11 deep learning architecture for detecting chronological age from dental panoramic X-ray images, which is vital for dentistry and forensic science. By leveraging a diverse dataset and employing preprocessing techniques, the model effectively extracts age-related dental features with high accuracy. This non-invasive age estimation framework enhances patient management and legal investigations. Future research will aim to improve prediction accuracy through larger datasets, transfer learning, and multimodal approaches.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - T. Lakshmi Praveena
AU  - M. Veera Kumari
AU  - D. B. Ramesh Kumar
AU  - Katukuri Poojitha
AU  - Kyatham Harshitha
AU  - Lasker Amulya
AU  - Balavari Sherlin Rozy
PY  - 2025
DA  - 2025/11/04
TI  - Chronological Age Detection Using Dental Panoramic Images
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 542
EP  - 550
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_47
DO  - 10.2991/978-94-6463-858-5_47
ID  - Praveena2025
ER  -