This review presents an in-depth study of the literature on segmentation methods applied in
dental imaging. Several works on dental image segmentation were studied and categorized …

Artificial intelligence has made substantial progress in medicine. Automated dental imaging
interpretation is one of the most prolific areas of research using AI. X-ray and infrared …

In this study, a novel AI system based on deep learning methods was evaluated to
determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks …

We propose using faster regions with convolutional neural network features (faster R-CNN)
in the TensorFlow tool package to detect and number teeth in dental periapical films. To …

The application of Artificial Intelligence in dental healthcare has a very promising role due to
the abundance of imagery and non-imagery-based clinical data. Expert analysis of dental …

In dentistry, radiological examinations help specialists by showing structure of the tooth
bones with the goal of screening embedded teeth, bone abnormalities, cysts, tumors …

Dental radiography plays an important role in clinical diagnosis, treatment and surgery. In
recent years, efforts have been made on develo** computerized dental X-ray image …

Tooth segmentation acts as a crucial and fundamental role in dentistry for doctors to make
diagnosis and treatment plans. In this paper, we propose a Two-Stage Attention …

In this paper, we demonstrate the application of Mask-RCNN, the state-of-the-art
convolutional neural network algorithm for object detection and segmentation to the oral …

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 …