COMMAX 2020 UiTM Kampus Kuala Terengganu

Caries detection in dental x-ray images is a difficult task to be done if only diagnose by naked eyes because of the intensity of the region of background image, ground teeth image and caries region, low image quality due to noise in the image and low contrast that make the image unclear to be seen that might takes time in detecting the caries. As we know that current technologies are evolving rapidly, those technologies can help medical lines especially dentists in their works. Many technologies are being used in detecting oral diseases such as radiography however there are also some limitations that need to overcome from the radiography. Therefore, a system has been proposed to detect caries in the dental x-ray images using Fuzzy c-means in order to overcome the limitations in radiography. In this study, a clustering algorithm known as Fuzzy c-means is proposed to detect caries in the dental x-ray images by grouping the region of background image, ground teeth and caries and will show the output of the image that contains caries and normal image that has no caries. From the system, Fuzzy c-means are proven to be one of the best clustering techniques in order to detect caries in the dental x-ray images based on the evaluation of efficiency and functionality of the system. For future work, this system can be improved by using high quality images and can be used in website to ease the usage of the system by the dentists in their works.