Computer-assisted detection of cemento-enamel junction in intraoral ultrasonographs

Nguyen, K.-C. T., Yan, Y., Kaipatur, N. R., Major, P. W., Lou, E. H., Punithakumar, K. and Le, L. H. (2021) Computer-assisted detection of cemento-enamel junction in intraoral ultrasonographs. Applied Sciences, 11(13), 5850. (doi: 10.3390/app11135850)

Abstract

The cemento-enamel junction (CEJ) is an important reference point for various clinical measurements in oral health assessment. Identifying CEJ in ultrasound images is a challenging task for dentists. In this study, a computer-assisted detection method is proposed to identify the CEJ in ultrasound images, based on the curvature change of the junction outlining the upper edge of the enamel and cementum at the cementum–enamel intersection. The technique consists of image preprocessing steps for image enhancement, segmentation, and edge detection to locate the boundary of the enamel and cementum. The effects of the image preprocessing and the sizes of the bounding boxes enclosing the CEJ were studied. For validation, the algorithm was applied to 120 images acquired from human volunteers. The mean difference of the best performance between the proposed method and the two raters’ measurements was an average of 0.25 mm with reliability ≥ 0.98. The proposed method has the potential to assist dental professionals in CEJ identification on ultrasonographs to provide better patient care.

• Item Type: Articles
• Keywords: High-frequency ultrasound, landmark detection, dento-periodontium, cemento-enamel junction, oral health, image processing.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Yan, Yuening

Creator Roles

Yan, Y.: Methodology, Software, Validation, Formal analysis, Resources, Writing – original draft, Writing – review and editing, Visualization

• Authors: Nguyen, K.-C. T., Yan, Y., Kaipatur, N. R., Major, P. W., Lou, E. H., Punithakumar, K., and Le, L. H.
• College/School: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• Journal Name: Applied Sciences
• Publisher: MDPI
• ISSN: 2076-3417
• ISSN (Online): 2076-3417
• Published Online: 23 June 2021
• Copyright Holders: Copyright © 2021 The Authors
• First Published: First published in Applied Sciences 11(13): 5850
• Publisher Policy: Reproduced under a Creative Commons License