Registration of Ultrasound and CBCT Images for Enhancing Tooth-Periodontinum Visualization: a Feasibility Study

Abstract

Malocclusion, a common dental anomaly, can lead to oral function issues such as difficulty in jaw movement, chewing, speech, and high susceptibility to periodontal diseases. High resolution cone-beam computed tomography (CBCT) images provide sharp visualization of the alveolar bone while delineation of gingiva is inferior. Ultrasound (US) images can delineate the thickness and extension of gingiva while partially showing the thickness of alveolar bones. Accurate registration of CBCT and US images of the tooth-periodontium would allow oral clinicians to visualize the gingiva and alveolar bone for proper diagnosis and orthodontic treatment. A probability-based point set registration using coherent point drift algorithm is proposed to tackle the problem of aligning CBCT and US images. The proposed algorithm was evaluated with images from human volunteers. The results indicate that the method is reasonably robust, and yield mean errors below the clinically accepted tolerance level of 0.5 mm. The limits of agreement between CBCT and US images measured in terms of landmark-based evaluations were [−0.22 mm, 0.26 mm] for intra-rater and [−0.19 mm, 0.21 mm] for inter-rater, respectively. More data are currently acquired to validate the accuracy and efficacy of the method.