Detection of Radiopaque Dental Materials From Lateral Cephalometric Images Using Canny Edge Detection and Nonlinear Gamma Correction

Abstract

Background: One of the most critical issues of cone-beam computed tomographic (CBCT) imaging is the presence of high-density subjects such as metal implants and dental fillings that consequently waste the benefit information in imaging due to their artifact developments. Given that 3D images of CBCT consist of a series of orthogonal images (images similar to lateral cephalometric images), the aim of this study was to offer an algorithm for detection of radiopaque dental materials from lateral cephalometric images to remove cupping artifacts from CBCT images. Methods: In this paper, lateral cephalometric images of Planmeca Scara 3 were used, each of which with 1259×1674 resolution in JPEG format. A total of 35 images of patients with radiopaque dental materials were selected. To decrease the time and image detection steps and for the purpose of acceleration we used Robinson edge detection and nonlinear gamma correction instead of filtering stage and noise reduction. Results: After applying the proposed algorithm to images and comparison with the acquired images, it was observed that the proposed algorithm was able to successfully detect radiopaque dental materials on lateral cephalometric images with high accuracy. Conclusions: Comparison of the reconstructed images and Table showed that the proposed algorithm was successful in detecting radiopaque dental materials on latral cephalometric images without reduction in image quality.