A Convolutional Neural Network Based Auto-Positioning Method For Dental Arch In Rotational Panoramic Radiography.

Abstract

Dental panoramic radiography (DPR), a widely used medical examination method, has its intrinsic weakness in high requirement to the positioning of patient. Although positioning devices like chin support can provide a relatively stable and guaranteed environment for exposure, problems including morphological differences of jaw between patients and their improper standing postures still put the reconstructed image at high risk of getting blurred, especially in the anterior segment of dental arch. This paper proposes a novel method based on convolutional neural network (CNN) to estimate the positioning error of patient's dental arch, and thereby reconstruct the panoramic image with the corrected dental curvature, so that the blur gets reduced. Experiment results demonstrate the method's effectiveness in providing reconstructed images of stable quality for further diagnosis.