Dental age estimation from panoramic X-ray images using statistical models

This paper presents an application of computer vision methods to dental age estimation based on the lower third right molar in panoramic X-ray images. For this purpose, two statistical computer vision models are adjusted and applied: Active Shape Model and Active Appearance Model. Both models use shape and appearance of the object to find the outer contour, with the only difference being in the way appearance is used. Statistical models are used to extract features describing the selected tooth, and neural network is used to provide dental age estimation using the features as input. Our own dataset was created, consisting of panoramic X-ray images with known age. A manual segmentation of the selected tooth has been performed for each image in the training set, and the obtained outer contours were used to train both models. Promising preliminary results are presented.