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Related Concept Videos

Assessment of the Mouth01:26

Assessment of the Mouth

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A thorough mouth assessment, including inspection and palpation of the lips, gums, tongue, tonsils, uvula, and pharynx, is crucial in detecting potential health issues. Diseases ranging from oral cancer to systemic conditions like diabetes could be identified early through careful oral examination. This article provides a detailed guide on conducting a comprehensive mouth assessment.
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The inspection begins with visually examining the mouth for symmetry, color, and size.
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Evaluating the Effects of Different Polishing Methods on Color Stability of Dental Restorations in Pediatric Dentistry
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Choosing the best image processing method for masticatory performance assessment when using two-coloured specimens.

G Vaccaro1, J I Pelaez2,3, J A Gil4

  • 1International Postgraduate School, School of Dentistry, Granada University, Granada, Spain.

Journal of Oral Rehabilitation
|March 13, 2016
PubMed
Summary
This summary is machine-generated.

This study identified the best image processing method for assessing masticatory performance using two-coloured chewing gum. The variance of the Hue histogram was found to be the optimal method for analyzing chewing efficiency.

Keywords:
chewing gumcomputer softwaredecision aidevidence-based dentistryimage processingmastication

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Area of Science:

  • Biomedical Engineering
  • Image Analysis
  • Dental Research

Background:

  • Masticatory performance assessment often uses two-coloured specimens and image processing.
  • Comparative studies on image processing methods for this purpose are lacking.
  • Standardized methods are needed to reliably evaluate chewing efficiency.

Purpose of the Study:

  • To develop and validate a procedure for selecting the optimal image analysis method for masticatory performance assessment.
  • To compare multiple image processing methods (IPMs) for analyzing two-coloured chewing gum specimens.
  • To identify the most effective IPM for quantifying chewing cycles.

Main Methods:

  • Analyzed 2000 digital images of red-white chewing gum specimens chewed for 3 to 25 cycles by 250 participants.
  • Evaluated 122 image processing methods based on feature extraction algorithms.
  • Applied statistical tests including Kolmogorov-Smirnov, ANOVA with Bonferroni correction, and Spearman's Rho correlation.
  • Utilized multiple criteria decision analysis (MCDA) to select the optimal IPM.

Main Results:

  • All tested IPMs yielded normally distributed measurements.
  • 116 IPMs detected significant differences among chewing mixing states.
  • 35 IPMs demonstrated moderate-to-high correlation with the number of chewing cycles.
  • The variance of the Hue histogram showed the highest correlation (ρ = 0.792) and the top MCDA score.

Conclusions:

  • A reliable procedure was established for selecting the optimal image processing method for masticatory performance analysis.
  • The variance of the Hue histogram is proposed as the optimal IPM for this specific two-coloured chewing gum.
  • This methodology can be adapted to identify optimal analysis approaches for different test foods.