Panoramic and periapical radiograph tools help dentists in diagnosing the most common
dental diseases, such as dental caries. Generally, dental caries is manually diagnosed by …

Objectives Deep convolutional neural networks (CNNs) are a rapidly emerging new area of
medical research, and have yielded impressive results in diagnosis and prediction in the …

Proximal dental caries are diagnosed using dental X-ray images. Unfortunately, the
diagnosis of proximal dental caries is often stifled due to the poor quality of dental X-ray …

Caries is the most well-known disease and relates to the oral health of billions of people
around the world. Despite the importance and necessity of a well-designed detection …

Based on an image dataset of 88 in-vivo dental images taken with an intra-oral camera, we
show that a Deep Learning model (Mask R-CNN) can detect and classify dental caries on …

Objectives: Deep learning methods have achieved impressive diagnostic performance in the
field of radiology. The current study aimed to use deep learning methods to detect caries …

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 …

Dental caries is a prevalent disease of the human oral cavity. Given the lack of research on
digital images for caries detection, we construct a caries detection dataset based on the …

Background. Dental caries is one of the major oral health problems and is increasing rapidly
among people of every age (children, men, and women). Deep learning, a field of Artificial …

Although visual examination (VE) is the preferred method for caries detection, the analysis of
intraoral digital photographs in machine-readable form can be considered equivalent to VE …