Assessment of YOLOv3 for caries detection in bitewing radiographs based on the ICCMS™ radiographic scoring system

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™).

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.

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).

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.

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.