Automated sex and age estimation from orthopantomograms using deep learning: A comparison with human predictions.

Journal: Forensic science international
Published Date: Jun 17, 2025

Abstract

INTRODUCTION/OBJECTIVES: Estimating sex and chronological age is crucial in forensic dentistry and forensic identification. Traditional manual methods for sex and age estimation are labor-intensive, time-consuming, and prone to errors. This study aimed to develop an automatic and robust method for estimating sex and chronological age from orthopantomograms using a multi-task deep learning network.

Authors

  • Inseok Kim
    Department of Advanced General Dentistry, Yonsei University College of Dentistry, Seoul, Republic of Korea. Electronic address: 20cboys@yonsei.ac.kr.
  • Sujin Yang
    Department of Advanced General Dentistry, College of Dentistry, Yonsei University, Seoul, Republic of Korea.
  • Yiseul Choi
    Department of Advanced General Dentistry, Yonsei University College of Dentistry, Seoul, Republic of Korea; Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Republic of Korea.
  • Hyeokhyeon Kwon
    PlayIdeaLab, 61, Yonsei-ro 2na-gil, Seodaemun-gu, Seoul, Republic of Korea.
  • Changmin Lee
    BK21-Y-BASE R&E Institute, School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Wonse Park
    Department of Advanced General Dentistry, College of Dentistry, Yonsei University, Seoul, Republic of Korea. Electronic address: wonse@yuhs.ac.

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