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Evaluation of dental plaque by quantitative digital image analysis system / 北京大学学报(医学版)
Journal of Peking University(Health Sciences) ; (6): 320-323, 2016.
Article in Chinese | WPRIM | ID: wpr-486591
ABSTRACT

Objective:

To analyze the plaque staining image by using image analysis software,to verify the maneuverability,practicability and repeatability of this technique,and to evaluate the influence of different plaque stains.

Methods:

In the study,30 volunteers were enrolled from the new dental students of Peking University Health Science Center in accordance with the inclusion criteria.The digital images of the anterior teeth were acquired after plaque stained according to filming standardization.The image analysis was performed using Image Pro Plus 7.0,and the Quigley-Hein plaque indexes of the anterior teeth were evaluated.

Results:

The plaque stain area percentage and the corresponding dental plaque in-dex were highly correlated,and the Spearman correlation coefficient was 0.776 (P<0.01 ).Intraclass correlation coefficients of the tooth area and plaque area which two researchers used the software to calcu-late were 0.956 and 0.930 (P<0.01).The Bland-Altman analysis chart showed only a few spots outside the 95%consistency boundaries.The different plaque stains image analysis results showed that the diffe-rence of the tooth area measurements was not significant,while the difference of the plaque area measure-ments significant (P<0.01).

Conclusion:

This method is easy in operation and control,highly related to the calculated percentage of plaque area and traditional plaque index,and has good reproducibility.The different plaque staining method has little effect on image segmentation results.The sensitive plaque stain for image analysis is suggested.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Journal of Peking University(Health Sciences) Year: 2016 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Journal of Peking University(Health Sciences) Year: 2016 Type: Article