Investigations on automated methods for dental plaque detection

by Reyes Silveyra, Lupita Jocelin

Type Thesis
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This thesis investigated different quantitative methods for dental plaque detection using digital imaging. Firstly, based on a commercially available two-tone disclosing, the concentration of the dyes in the blue disclosing solution was calculated. This blue dye was used to disclose dental plaque accumulated on natural teeth and complete upper dentures (on two different backgrounds). Digital images were acquired under visible light, in the n-IR spectrum and with a narrow band-pass interference …

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Summary

This thesis investigated different quantitative methods for dental plaque detection using digital imaging. Firstly, based on a commercially available two-tone disclosing, the concentration of the dyes in the blue disclosing solution was calculated. This blue dye was used to disclose dental plaque accumulated on natural teeth and complete upper dentures (on two different backgrounds). Digital images were acquired under visible light, in the n-IR spectrum and with a narrow band-pass interference (NIB) filter tuned to the absorption spectrum of the blue dye. The results showed that disclosing dyes and disclosed dental plaque are transparent in the n-IR spectrum whilst the NIB filter maximised the contrast of dental plaque in the images when using the blue stain. A number of computerised segmentation methods were applied to these images showed automation of dental plaque detection to identify reliable methods to quantify plaque coverage. Although minor human intervention was still required in the segmentation process, the continuous development of new software promises that full automation in plaque quantification is almost a reality. Finally, analysis of the inter- and intra-examiner reliability of the commonly used Quigley and Hein index showed moderate reliability, highlighting the need for automated, quantitative and more reproducible methodology.

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Edition Statements

  • Publication Date:2012

Thesis Information

  • Degree:Ph.D.
  • University:University of Birmingham

Publication Statements

  • Language:eng
  • Publication Date:2012

Edition Identifiers

  • ethos:547577

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