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 …

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

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 …

Objectives To evaluate a fully deep learning mask region-based convolutional neural
network (R-CNN) method for automated tooth segmentation using individual annotation of …

Objective: This study evaluated the use of a deep-learning approach for automated
detection and numbering of deciduous teeth in children as depicted on panoramic …

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 …

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 …

In the development of digital multimedia, the importance and impact of image processing
and mathematical morphology are well documented in areas ranging from automated vision …