Defense Date

2014

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Engineering

First Advisor

Rosalyn Hobson Hargraves

Abstract

Dental caries are one of the most prevalent chronic diseases. Worldwide 60 to 90 percent of school children and nearly 100 percent of adults experienced dental caries. The management of dental caries demands detection of carious lesions at early stages. The research of designing diagnostic tools in caries has been at peak for the last decade. This research aims to design an automated system to detect and score dental caries according to the International Caries Detection and Assessment System (ICDAS) guidelines using the optical images of the occlusal tooth surface. There have been numerous works that address the problem of caries detection by using new imaging technologies or advanced measurements. However, no such study has been done to detect and score caries with the use of optical images of the tooth surface. The aim of this dissertation is to develop image processing and machine learning algorithms to address the problem of detection and scoring the caries by the use of optical image of the tooth surface.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

8-19-2014

Available for download on Sunday, August 18, 2019

Included in

Dentistry Commons

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