OBJECTIVES: Pulpal calcifications are discrete hard calcified masses of varying sizes in the dental pulp cavity. This study is aimed at measuring the performance of the YOLOv4 deep learning algorithm to automatically determine whether there is calcif...
Intelligent robotics and expert system applications in dentistry suffer from identification and detection problems due to the non-uniform brightness and low contrast in the captured images. Moreover, during the diagnostic process, exposure of sensiti...
BACKGROUND: This study aims to verify the effectiveness of a deep neural network (DNN) in automatically identifying pulp calcification on cone beam computed tomography (CBCT) images.
OBJECTIVES: Pulp stones are ectopic calcifications located in pulp tissue. The aim of this study is to introduce a novel method for detecting pulp stones on panoramic radiography images using a deep learning-based two-stage pipeline architecture.