Detection of dental caries in oral photographs taken by mobile phones based on the YOLOv3 algorithm.

ABSTRACT:

Background

The aim of this study was to explore the value of using the YOLOv3 algorithm for detection and diagnosis of dental caries in oral photographs taken with mobile phones.

Methods

Oral photographs taken with the mobile phones of 570 patients were used as 3 datasets: the augmented images (n=3,990), the enhanced images (n=3,990), and the combined augmented and enhanced images (n=7,980). Oral photographs taken by mobile phones from another 70 patients were used as an independent test set. We used the YOLOv3 network for migration learning for modelling. Diagnostic precision, recall, F1-score, and mean average precision (mAP) were calculated to obtain the detection and diagnostic performance of the YOLOv3 algorithm.

Results

After 3 independent training, the mAP valu

SUBMITTER: Ding B 

PROVIDER: S-EPMC8640896 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature