Objectives Detecting caries lesions is challenging for dentists, and deep learning models
may help practitioners to increase accuracy and reliability. We aimed to systematically …

Dental disease evaluation and clinical assessment are frequently accomplished through
radiographic penetration. The difficulty of obtaining an accurate clinical diagnosis from …

Objectives It is with a great prospect to develop an auxiliary diagnosis system for dental
periapical radiographs based on deep convolutional neural networks (CNNs), and the …

Early diagnosis of dental caries progression can prevent invasive treatment and enable
preventive treatment. In this regard, dental radiography is a widely used tool to capture …

In dentistry, practitioners interpret various dental X-ray imaging modalities to identify tooth-
related problems, abnormalities, or teeth structure changes. Another aspect of dental …

Dental caries is one of the most chronic diseases involving the majority of the population
during their lifetime. Caries lesions are typically diagnosed by general dentists relying only …

Nearly 3.5 billion humans have oral health issues, including dental caries, which requires
dentist-patient exposure in oral examinations. The automated approaches identify and …

Objectives In recent years, periodontitis, and dental caries have become common in humans
and need to be diagnosed in the early stage to prevent severe complications and tooth loss …

Objectives In this study, we aimed to integrate tooth number recognition and caries detection
in full intraoral photographic images using a cascade region-based deep convolutional …

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 …