Analysis Of Image Segmentation Techniques For Dental Radiographs

Abstract

Now a days, one of the most prevalent dental illnesses affecting people of all ages worldwide is dental caries. It might be difficult to identify dental caries in its early stages using dental xray or radiovisiography (RVG) pictures. Nearly all medical areas employ deep learning to anticipate or identify certain disorders. In this study, a K-means clustering for image segmentation was proposed and examined. This study has shown that image enhancement methods are crucial for enhancing the quality of dental radiograph pictures. The proposed k- means model algorithm has been done, with better accuracy.