A framework to integrate deep learning and an ethnicity-specific reference data set for reliable dental age estimation from digital panoramic radiographs

Kuen Wai MA; Jiajun ZHU; Hai Ming WONG

doi:10.1631/ENG.ITEE.2026.0013

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A framework to integrate deep learning and an ethnicity-specific reference data set for reliable dental age estimation from digital panoramic radiographs

Regular Papers | Updated：2026-08-28

- A framework to integrate deep learning and an ethnicity-specific reference data set for reliable dental age estimation from digital panoramic radiographs
- A framework to integrate deep learning and an ethnicity-specific reference data set for reliable dental age estimation from digital panoramic radiographs
- ENGINEERING Information Technology & Electronic Engineering Vol. 27, Issue 8, Pages: 1-14(2026)
- Affiliations：
  
  Faculty of Dentistry, The University of Hong Kong, Hong Kong 999077, China
  Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
  Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Zhejiang Key Laboratory of Oral Biomedical, Hangzhou 310000, China
  Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou 310000, China
- Author bio：
  
  ✉Jiajun ZHU, zhujj@zju.edu.cn
  Hai Ming WONG, wonghmg@hku.hk
- Funds：
- DOI：10.1631/ENG.ITEE.2026.0013
  CLC： TP183;R783.1
- Received：16 January 2026，
  
  Revised：2026-05-28，
  
  Online First：26 August 2026，
  
  Published：01 August 2026
- Accepted：
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Kuen Wai MA, Jiajun ZHU, Hai Ming WONG. A framework to integrate deep learning and an ethnicity-specific reference data set for reliable dental age estimation from digital panoramic radiographs[J]. ENGINEERING Information Technology & Electronic Engineering, 2026, 27(8): 1-14.
DOI：

Kuen Wai MA, Jiajun ZHU, Hai Ming WONG. A framework to integrate deep learning and an ethnicity-specific reference data set for reliable dental age estimation from digital panoramic radiographs[J]. ENGINEERING Information Technology & Electronic Engineering, 2026, 27(8): 1-14. DOI： 10.1631/ENG.ITEE.2026.0013.

摘要

Abstract

Automated dental age estimation is essential for clinical dentistry. However

traditional methods like Demirjian’s tooth development stage (TDS) require time-consuming manual annotation by trained experts. Moreover

population differences in dental development patterns can significantly affect the accuracy of age estimation

highlighting the need for an ethnicity-specific reference data set (RDS). This study aims to use deep neural networks (DNNs) for automated estimation of Demirjian’s TDS of molars on digital panoramic radiographs

integrating the most complete southern Chinese RDS for ethnicity-appropriate dental age assessment. Panoramic radiographs from individuals aged 2 to 25 years are annotated for molar TDS and used to train eight DNN architectures

including AlexNet

DenseNet-201

and ResNet-50. DenseNet-201 achieves the highest accuracy of 93% in classifying molar TDS. Most misclassifications involve adjacent stages. The integrated mean dental age (IMDA) is obtained by mapping the predicted molar TDS using the southern Chinese RDS. The mean difference and correlation coefficient between the estimated IMDA from the best-performing DNN (AlexNet) and chronological age are -0.063 years (-3.3 weeks) and

=0.898 (

0.001)

respectively. These findings demonstrate that combining DNN for TDS estimation with ethnic-specific RDS enables accurate and reliable dental age assessment.

关键词

Keywords

references

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