Measuring panoramic radiomorphometric indices for mandible bone using active shape model and Bayesian information criterion‐support vector machine

Abstract

This article proposes an automatic method based on a combination of active shape model (ASM) and nonlinear support vector machine (SVM) accompanied with Bayesian information criterion which is utilized in order to measure radiomorphometric indices for digital X-ray panoramic system. After omitting Poisson noise of input images, the image is divided. It attempts to choose suitable region of interest (ROI) in order to extract indices. This region becomes small and smaller during some steps until the final ROI is found and the mandible's cortex and ramus are detected. Finally, because of measuring the required parameters, ASM and SVM are used in order to evaluate exact setting of the detected region. Experimental results show no significant differences between right and left sides in terms of mental index (MI), panoramic mandibular index (PMI), gonial angle (GA), gonial index (GI), antegonial index (AGI), ramus height (RH), and ramus width (RW); however, in terms of GI and AGI for both sexes. There are significant differences between men and women for all indices in the mandible (P-value <.05). There was a mild negative significant correlation among GA and MI, GI, AGI and a moderate negative significant correlation among GA and PMI, RH, RW for both genders (P-value <.05). Besides, it has been shown measuring the panoramic indices provide useful information about trauma and prediction of asymptomatic subjects with osteoporosis at an earlier step.