Fully automatic teeth segmentation in adult OPG images

Abstract

This work addresses the problem of segmenting teeth in panoramic dental images. Random forest regression voting constrained local models were applied firstly to locate the mandible and the approximate pose of each tooth, and secondly to locate the full outline of each individual tooth. An automatically computed quality-of-fit measure was proposed to identify missing teeth. The system was evaluated using 346 manually annotated images containing adult-stage mandibular teeth. Encouraging results were achieved for detecting missing teeth. The system achieved state-of-the-art performance in locating the outline of present teeth with a median point-to-curve error of 0.2 mm for each of the teeth.