One of the critical aspects of oral hygiene management in orthodontic patients with fixed appliances is the identification of dental plaque. In this paper, we present AIRC-LABDEN, a new multi-modal dental dataset specifically designed for the detection and quantification of plaque accumulation on the teeth of patients wearing orthodontic brackets using deep learning. The dataset integrates 10,450 high-resolution intraoral images from 148 patients with their corresponding anonymized clinical records, providing demographic and treatment-related data to support comprehensive analysis. All images were acquired using professional photographic equipment and standardized imaging protocols. Each image is annotated with labels indicating the presence of plaque on individual teeth, a process involving two dentists with a minimum of five years of clinical experience. By facilitating the development of multi-modal plaque detection systems, this asset helps orthodontic patients improve their oral care routines while providing a practical foundation for embedding authentic data into dental studies and academic frameworks.
Anh et al. (Fri,) studied this question.