Dental caries is tooth decay caused by bacterial infections. It is commonly known as cavities. This infection causes demineralization and hence destruction of the teeth. Diagnosis of dental caries is conventionally facilitated with radiographical films. This research aims to develop some algorithm of the mMG method in identifying dental caries based using digital panoramic dental x-ray images. This paper presents an algorithm of using digital panoramic dental x-ray images to detect dental caries. Type of algorithm used in this study is normal mMG, Enhancement mMG, and Smooth mMG. This study makes use of MATLAB and it performs dental caries detection in three algorithms. A dataset of 225 digital panoramic dental x-ray images in .png format is used to edge detection of the object in dental. The results are helpful to identify such caries from the tooth.
<span>Panoramic X-Ray produces produces the most common oral digital radiographic image that it used in dentistry practice. The image can further improve accuracy compared to analog one. This study aims to establish proximal caries edge on enhancement images so they can be easily recognized. The images were obtained from the Department of Radiology, General Hospital of M. Djamil Padang Indonesia. Total file of images to be tested were 101. Firstly, the images are analyzed by dentists who practiced at Segment Padang Hospital Indonesia. They concluded that there is proximal caries in 30 molar teeth. Furthermore, the images were processed using Matlab software with the following steps, i.e. cropping, enhancement, edge detection, and edge enhancement. The accuracy rate of detection of edge enhancement images being compared with that of dentist analysis was 73.3%. In the edge enhancement images proximal caries edge can be found conclusively in 22 teeth and dubiously in eight teeth. The results of this study convinced that edge enhancement images can be recommended to assist dentists in detecting proximal caries. </span>
This study aims to perform the sharpening of the dental x-ray image in the form of a panoramic dental x-ray. The method used in this study was segmentation morphology consisting of the dilation, erosion and gradient process. This study also developed a process of morphology gradient of subtracting morphology dilation results with the results of morphology erosion dilation in iterating basis. The results achieved indicate that the image enhancement process in each iteration stage can display caries objects clearly, making it easier to identify proximal caries. In this study have been compiled a looping morphology gradient algorithm which is called multiple morphology gradient.
This study aims to facilitate the identification of proximal caries in the Panoramic Dental X-Ray image. Twenty-seven X-Ray images of proximal caries were elaborated. The images in digital form were processed using Matlab and Multiple Morphological Gradients. The process produced sharper images and clarifies the edges of the objects in the images. This makes the characteristics of the proximal caries and the caries severity can be identified precisely.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.