Identification and volume estimation of dental caries using CT image

Early detection of dental caries is vital as it causes several fatal diseases like cancer if it spreads into the root of the teeth. Therefore, early detection, tracking, and testing the depth of carious lesion may be lifesaving. In this paper, a carious detection method has been presented, and the volume of caries has been investigated. We have applied K-means clustering and threshold method for segmentation and utilized Computed Tomography (CT) images in order to construct the three-dimensional view of the carious lesion which is an integral part of the diagnosis of dental cavity. Result shows that the average Peak Signal-to-Noise Ratio (PSNR) has been obtained 19.98 and 20 by applying K-means clustering and threshold method respectively along with satisfactory visual interpretation of the three-dimensional structure of dental carries. This contribution can be applied for several other medical detection purposes with a slight adjustment.