Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6891537 | Computer Methods and Programs in Biomedicine | 2016 | 18 Pages |
Abstract
Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ÎE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as “gold standard” to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value = 0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Bhornsawan Thanathornwong, Siriwan Suebnukarn, Kan Ouivirach,