Dental Radiography Analysis and Diagnosis using YOLOv8

Panoramic dental radiography is a widely used diagnostic tool in dentistry that provides valuable information about a patient’s oral health. These two-dimensional images of the entire upper and lower jaw offer a comprehensive view of the oral cavity and allow for the diagnosis of various conditions, including tooth decay, periodontal diseases, and jaw abnormalities. The use of Gaussian and Laplacian pyramids for image enhancement is a common technique employed in this field. The GVF Snake technique, a computer vision approach, is utilized for dental radiograph analysis. It has proven effective in tasks such as tooth segmentation, root canal detection, and tooth movement analysis, improving the accuracy and efficiency of dental diagnosis and treatment planning. Manual annotation, model training, and deployment are facilitated by the computer vision platform Roboflow. The YOLOv8 training model, chosen for this research, has shown promising results with a precision of 82.36% in detecting and classifying dental diseases such as cavities, periodontal disease, and oral cancers. By training the model on a large dataset of dental radiographs, it can accurately identify different types of dental diseases, leading to early detection and more effective treatment. Overall, the integration of deep learning algorithms, image enhancement techniques, computer vision, and machine learning methods holds great potential in improving patient outcomes by enabling early detection, accurate diagnosis, and better management of dental conditions.