A Mask-based Cavity Detection Model for Dental X-ray Image

The dental images are significantly analyzed to upgrade and evaluate the medical images for appropriate investigation. The dental cavity is the most common disease discovered from the early stage. For early identification of cavity is the best prevention from tooth decay or cancer if it is transmitted to the root of the teeth. In this paper, a model is proposed to help the dentist to detect the cavity from radiographic images. The model tries to overcome the difficulty that arises in edge extraction during the root canal treatment. The proposed algorithm preceded by the pre-processing stage, which uses the grayscale version and contrast enhancement of the x-ray image. It adopts the concept of masking for detecting a cavity and contour the cavity. The model provides the image with cavity identification as the output for easy visualization.