Dental caries detection in children using intraoral scans and deep learning

Abstract

Objective: This study aimed to demonstrate the use of deep learning for automating caries detection using intraoral scan data from children and to evaluate diagnostic agreement between the models’ predictions and dental practitioner assessments on 3D models. Methods: Intraoral scans were collected from two cohorts at Murdoch Children's Research Institute. Two researchers annotated scan meshes using the International Caries Classification and Management System. A pre-processing pipeline converted the data into a 2D format. Carious teeth from the first cohort (n = 332) were split at the participant level into training (n = 192), validation (n = 63), and test (n = 77) sets. An Attention U-Net w..