Detection of Tooth Decay Using Panoramic X-ray

The most prevalent non-communicable disease in people is dental caries. Dental caries can lead to tooth extraction, often result in pain and infections, and are hazardous to general health in many ways. There are numerous image-processing methods that can be used to find dental diseases. We describe a method for identifying tooth cavities in panoramic x-rays in this paper. A panoramic dental X-ray, often called a panoramic radiograph or simply a panorex, gives a detailed picture of the teeth, upper and lower jaws, TMJ, and sinuses in the mouth. In this study, cavity detection in panoramic images is accomplished using the unsupervised learning algorithm kmeans clustering. The input image must first be preprocessed in order to improve the image data and eliminate unwanted noise. The preprocessed image is transformed into a binary image. The binary image is switched to the Kmeans clustering technique in the third step. For accurate cavity detection in step four, clustered images are moved to the morphological dilation and erosion process. For cavity detection, the above stages are employed in the MATLAB program. It is a technique that aids the medical professional in effectively diagnosing and identifying dental disorders. According to the study, an effective computerized image processing system can improve the efficiency of medical professionals and decrease errors and diagnosis time. The 116 images are shown on the Kaggle platform, which is where the image datasets are stored.