Abstract
Objectives
To assess the feasibility of the YOLOv3 model under the intersection over union (IoU) thresholds of 0.5 (IoU50) and 0.75 (IoU75) for caries detection in bitewing radiographs based on the International Caries Classification and Management System (ICCMS™).
Materials and methods
We trained the YOLOv3 model by feeding 994 annotated radiographs with the IoU50 and IoU75 thresholds. The testing procedure (n = 175) was subsequently conducted to evaluate the model’s prediction metrics on caries classification based on the ICCMS™ radiographic scoring system.
Results
Regarding the 4-class classification representing caries severity, YOLOv3 could accurately detect and classify enamel caries and initial dentin caries (class RA) (IoU50 vs IoU75: precision, 0.75 vs 0.71; recall, 0.67 vs 0.64). Concerning the 7-class classification signifying specific caries depth (class 0, healthy tooth; classes RA1-3, initial caries affecting outer half, inner half of enamel, and the outer 1/3 of dentin; class RB4, caries extending to the middle 1/3 of dentin; classes RC5-6, extensively cavitated caries affecting the inner 1/3 of dentin and involving the pulp chamber), YOLOv3 could accurately detect and classify caries with pulpal exposure (class RC6) (IoU50 vs IoU75: precision, 0.77 vs 0.73; recall, 0.61 vs 0.57) but it failed to predict the outer half of enamel caries (class RA1) (IoU50 vs IoU75: precision, 0.35 vs 0.32; recall, 0.23 vs 0.21).
Conclusions
YOLOv3 yielded acceptable performances in both IoU50 and IoU75. Although the performance metrics decreased in the 7-class detection, the two thresholds revealed comparable results. However, the model could not consistently detect initial-stage caries affecting the outermost surface of the enamel.
Clinical relevance
YOLOv3 could be implemented to detect and classify dental caries according to the ICCMS™ classification with acceptable performances to assist dentists in making treatment decisions.
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Data Availability
Due to privacy and ethical concerns, neither the data nor the source of the data can be made available.
Change history
17 January 2023
A Correction to this paper has been published: https://doi.org/10.1007/s00784-023-04865-y
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Acknowledgements
The authors thank the following individuals for their expertise and assistance throughout all aspects of the study and for their help in writing the manuscript: Dr. Robert Batzinger from the Department of Information Technology, the International College, Payap University and Dr. Thanapat Sastraruji from the Faculty of Dentistry, Chiang Mai University.
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All authors have read and approved the manuscript.
Wannakamon Panyarak: conceptualization, data curation, investigation, formal analysis, methodology, writing—original draft preparation, writing—review, and editing; Wattanapong Suttapak: software, validation, visualization, writing—review, and editing; Kittichai Wantanajittikul: methodology, resources, visualization, writing—review, and editing; Arnon Charuakkra and Sangsom Praparasatok: data curation, writing—review, and editing.
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This article reports a study that involved radiographs of patients. All the procedures performed in accordance with the ethical standards of the Institutional Ethical Review Board of the Faculty of Dentistry, Chiang Mai University approved the study design (approval no. 22/2021).
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Informed consent was waived in accordance with the retrospective nature of the study.
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The original version of this article was revised: This article was originally published with incorrect F1 scores and AP values for both IOU50 and IOU75 in Table 2 on page 6 and the Results section on pages 6-7.
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Panyarak, W., Suttapak, W., Wantanajittikul, K. et al. Assessment of YOLOv3 for caries detection in bitewing radiographs based on the ICCMS™ radiographic scoring system. Clin Oral Invest 27, 1731–1742 (2023). https://doi.org/10.1007/s00784-022-04801-6
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DOI: https://doi.org/10.1007/s00784-022-04801-6