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Demineralization Depth Using QLF and a Novel Image Processing Software

Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was t...

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Detalles Bibliográficos
Autores principales: Wu, Jun, Donly, Zachary R., Donly, Kevin J., Hackmyer, Steven
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2860768/
https://www.ncbi.nlm.nih.gov/pubmed/20445755
http://dx.doi.org/10.1155/2010/958264
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author Wu, Jun
Donly, Zachary R.
Donly, Kevin J.
Hackmyer, Steven
author_facet Wu, Jun
Donly, Zachary R.
Donly, Kevin J.
Hackmyer, Steven
author_sort Wu, Jun
collection PubMed
description Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was to study this correlation to estimate demineralization depth. Extracted teeth were collected. Artificial caries-like lesions were created and imaged with QLF. Novel image processing software was developed to measure the largest percent of fluorescence loss in the region of interest. All teeth were then sectioned and imaged by polarized light microscopy. The largest depth of demineralization was measured by NIH ImageJ software. The statistical linear regression method was applied to analyze these data. The linear regression model was Y = 0.32X + 0.17, where X was the percent loss of fluorescence and Y was the depth of demineralization. The correlation coefficient was 0.9696. The two-tailed t-test for coefficient was 7.93, indicating the P-value = .0014. The F test for the entire model was 62.86, which shows the P-value = .0013. The results indicated statistically significant linear correlation between the percent loss of fluorescence and depth of the enamel demineralization.
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spelling pubmed-28607682010-05-05 Demineralization Depth Using QLF and a Novel Image Processing Software Wu, Jun Donly, Zachary R. Donly, Kevin J. Hackmyer, Steven Int J Dent Research Article Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was to study this correlation to estimate demineralization depth. Extracted teeth were collected. Artificial caries-like lesions were created and imaged with QLF. Novel image processing software was developed to measure the largest percent of fluorescence loss in the region of interest. All teeth were then sectioned and imaged by polarized light microscopy. The largest depth of demineralization was measured by NIH ImageJ software. The statistical linear regression method was applied to analyze these data. The linear regression model was Y = 0.32X + 0.17, where X was the percent loss of fluorescence and Y was the depth of demineralization. The correlation coefficient was 0.9696. The two-tailed t-test for coefficient was 7.93, indicating the P-value = .0014. The F test for the entire model was 62.86, which shows the P-value = .0013. The results indicated statistically significant linear correlation between the percent loss of fluorescence and depth of the enamel demineralization. Hindawi Publishing Corporation 2010 2010-04-28 /pmc/articles/PMC2860768/ /pubmed/20445755 http://dx.doi.org/10.1155/2010/958264 Text en Copyright © 2010 Jun Wu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wu, Jun
Donly, Zachary R.
Donly, Kevin J.
Hackmyer, Steven
Demineralization Depth Using QLF and a Novel Image Processing Software
title Demineralization Depth Using QLF and a Novel Image Processing Software
title_full Demineralization Depth Using QLF and a Novel Image Processing Software
title_fullStr Demineralization Depth Using QLF and a Novel Image Processing Software
title_full_unstemmed Demineralization Depth Using QLF and a Novel Image Processing Software
title_short Demineralization Depth Using QLF and a Novel Image Processing Software
title_sort demineralization depth using qlf and a novel image processing software
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2860768/
https://www.ncbi.nlm.nih.gov/pubmed/20445755
http://dx.doi.org/10.1155/2010/958264
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