Automatic detection of teeth and dental treatment patterns on dental panoramic radiographs using deep neural networks

Forensic Sciences Research

Thomhert Suprapto Siadari¹  Sam-Sun Lee²  Min-Suk Heo²  Won-Jin Yi²  Hye-Ran Choi²  Kyung-Hoe Huh²  Jo-Eun Kim³ 

[1] Artificial Intelligence Research Centre, Digital Dental Hub Incorporation, Seoul, Republic of Korea;Department of Oral and Maxillofacial Radiology and Dental Research Institute, School of Dentistry, Seoul National University, Seoul, Republic of Korea;Department of Oral and Maxillofacial Radiology, Seoul National University Dental Hospital, Seoul, Republic of Korea;

关键词: Forensic sciences;    forensic odontology;    individual identification;    disaster victim identification;    radiography;    deep learning;   

DOI  :  10.1080/20961790.2022.2034714

来源: DOAJ

【 摘 要 】

Disaster victim identification issues are especially critical and urgent after a large-scale disaster. The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on dental panoramic radiographs (DPRs) using deep learning to promote its applicability as human identifiers. A total of 1 638 DPRs, of which the chronological age ranged from 20 to 49 years old, were collected from January 2000 to November 2020. This dataset consisted of natural teeth, prostheses, teeth with root canal treatment, and implants. The detection of natural teeth and dental treatment patterns including the identification of teeth number was done with a pre-trained object detection network which was a convolutional neural network modified by EfficientDet-D3. The objective metrics for the average precision were 99.1% for natural teeth, 80.6% for prostheses, 81.2% for treated root canals, and 96.8% for implants, respectively. The values for the average recall were 99.6%, 84.3%, 89.2%, and 98.1%, in the same order, respectively. This study showed outstanding performance of convolutional neural network using dental panoramic radiographs in automatically identifying teeth number and detecting natural teeth, prostheses, treated root canals, and implants.

【 授权许可】

Unknown