Diagnosing dental caries plays a pivotal role in preventing and treating tooth decay.
However, traditional methods of diagnosing caries often fall short in accuracy and efficiency …

Objectives Artificial intelligence (AI) is an emerging field in dentistry. AI is gradually being
integrated into dentistry to improve clinical dental practice. The aims of this sco** review …

Introduction The aim of this study was to leverage label-efficient self-supervised learning
(SSL) to train a model that can detect ECR and differentiate it from caries. Methods …

Oral diseases are very prevalent worldwide and affect people of all ages. Dentists depend
on x-rays to study the characteristics of oral diseases. The segmentation and analysis of …

Objectives: The aim of the study was to evaluate the efficacy of traditional supervised
learning (SL) and semi-supervised learning (SSL) in the classification of mandibular third …

This perspective is an overview of the recent advances in teeth microcrack (MC) research,
where there is a clear tendency towards a shift from two-dimensional (2D) to three …

Artificial intelligence (AI) is revolutionizing the field of oral and dental healthcare by offering
innovative tools and techniques for optimizing diagnosis, treatment planning, and patient …

An innovative approach to enhance image alignment through affine transformation, allowing
images to be rotated from 0 to 135 degrees. This transformation is a crucial step in improving …

The development of mobile and on the edge applications that embed deep convolutional
neural models has the potential to revolutionise healthcare. However, most deep learning …

Deep learning approaches for tooth segmentation employ convolutional neural networks
(CNNs) or Transformers to derive tooth feature maps from extensive training datasets. Tooth …