Automatic tooth identification in dental panoramic images with atlas-based models

Abstract

After catastrophes and mass disasters, accurate and efficient identification of decedents requires an automatic system which depends upon strong biometrics. In this paper, we present an automatic tooth detection and labeling system based on panoramic dental radiographs. Although our ultimate objective is to identify decedents by comparing the postmortem and antemortem dental radiographs, this paper only involves the tooth detection and the tooth labeling stages. In the system, the tooth regions are first determined and the detection module runs for each region individually. By employing the sliding window technique, the Haar features are extracted from each window and the SVM classifies the windows as tooth or not. The labeling module labels the candidate tooth positions determined by the SVM with an atlas-based model and the final tooth positions are inferred. The novelty of our system is combining the atlas-based model with the SVM under the same framework. We tested our system on 35 panoramic images and the results are promising.