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

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 applicabil...

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Bibliographic Details
Published in:Forensic sciences research 2022-07, Vol.7 (3), p.456-466
Main Authors: Choi, Hye-Ran, Siadari, Thomhert Suprapto, Kim, Jo-Eun, Huh, Kyung-Hoe, Yi, Won-Jin, Lee, Sam-Sun, Heo, Min-Suk
Format: Article
Language:English
Subjects:
artificial intelligence
Deep learning
Dental prosthetics
disaster victim identification
Endodontics
Forensic odontology
Forensic sciences
individual identification
Neural networks
Prostheses
Radiography
Regular Papers
Root canals
Teeth
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Summary: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. It is useful to use dental panoramic radiographs to perform the disaster victim identification (DVI).
ISSN:2096-1790
2471-1411
DOI:10.1080/20961790.2022.2034714