Gender inference of orthopantomogram based on deep learning
10.13618/j.issn.1001-5728.2023.06.002
- VernacularTitle:基于深度学习对口腔全景摄影片进行性别推断的研究
- Author:
Yanjie DING
1
;
Yuxin HE
;
Wei WANG
;
Xiao ZHANG
;
Ziyi LI
;
Aji GUO
;
Shilin ZHANG
;
Wenli SHI
;
Canan WU
;
Bo JIN
Author Information
1. 川北医学院基础医学与法医学研究所,四川 南充 637000
- Keywords:
Forensic anthropology;
Gender inference;
Orthopantomogram;
Deep learning
- From:
Chinese Journal of Forensic Medicine
2023;38(6):614-618,622
- CountryChina
- Language:Chinese
-
Abstract:
Objective Explore the feasibility and accuracy of using deep learning techniques for gender inference in panoramic dental radiography images of Chinese Han population.Methods A total of 10,600 OPG images from Han individuals aged 18 to 70(5,300 males and 5,300 females)were collected and randomly divided into training set,validation set,and test set in an 8:1:1 ratio.MobileNetV2,Swin Transformer Small,and Swin Transformer Tiny models were trained,and the classification performance of the models was evaluated and visually displayed using accuracy,F1 score,and Grad-CAM algorithm.Results The accuracy of MobileNetV2,Swin Transformer Small,and Swin Transformer Tiny models was 97.57%,95.13%,and 96.28%respectively,with MobileNetV2 model showing the best overall performance.The Grad-CAM algorithm revealed that male OPG images mainly focused on the left and right mandibular branches and alveolar bone,while female OPG images mainly focused on the maxillary sinus,left mandibular branch,and posterior alveolar bone.Conclusion This study demonstrates that the gender inference model based on deep learning techniques for OPG images of Chinese Han population has high accuracy and generalization ability,providing a new approach for forensic gender determination in forensic medicine.
