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Related Experiment Video

Updated: Jun 5, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
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Machine-Learning-Based Spectral Modeling: A Biomimetic Guide for Enhancing Esthetics.

L J Herrera1, R Ghinea2,3, M M Perez2

  • 1Department of Computer Engineering, Automatics and Robotics, School of Technology and Telecommunication Engineering, University of Granada, Granada, Spain.

Journal of Esthetic and Restorative Dentistry : Official Publication of the American Academy of Esthetic Dentistry ... [Et Al.]
|December 8, 2024
PubMed
Summary

Related Concept Videos

Aliasing01:18

Aliasing

117
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
117

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Assessing Color Inconstancy of CAD/CAM Materials: Influence of CIE White LED Illuminants and Substrate Shade.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]·2026
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Effect of Successive Bleaching Treatments Followed by Staining on Color, Whiteness, and Translucency of Polymer-Based CAD-CAM Materials.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]·2026
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Interrelational Proteomic Sequence Features Enhance Predictive Modeling: Application to COVID-19 Severity.

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Masking Ability of CAD-CAM Materials at Different Thicknesses: A Study on Color, Translucency, and Infinite Optical Thickness.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]·2025
This summary is machine-generated.

Computer-optimized dental shade guides with 4-6 tabs significantly outperformed physical guides in accuracy. This biomimetic approach offers better shade matching with fewer options.

Area of Science:

  • Dental materials science
  • Color science
  • Computational modeling

Background:

  • Accurate dental shade matching is crucial for aesthetic restorations.
  • Current dental shade guides have limitations in coverage and distribution.
  • Developing optimized shade systems is essential for improving clinical outcomes.

Purpose of the Study:

  • To develop and evaluate computer-optimized dental shade guide models.
  • To compare the performance of these models against established physical shade guides.
  • To provide guidelines for optimal coverage and distribution of dental color models.

Main Methods:

  • Utilized the Fuzzy C-Means (FCM) algorithm for tab optimization in CIELAB color space.
  • Implemented spectral reconstruction and minimization processes to reduce Coverage Error (CE₀₀) and Maximum Error (ME₀₀).
Keywords:
Fuzzy C‐Means (FCM) algorithmcolordental shade guidesmachine learningspectral modeling

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  • Compared optimized models (1-10 tabs) with VITA classical, Linearguide 3D-Master, and Bleachedguide 3D-Master shade guides.

    • Main Results:

    • Optimized 4-tab and 6-tab models demonstrated superior performance over tested physical shade guides.
    • The 4-tab model (CE₀₀=2.2, ME₀₀=7.1) outperformed the best physical guide (Linearguide 3D-Master CE₀₀=2.3).
    • Increasing the number of tabs in optimized models significantly improved CE₀₀ (p ≤ 0.05).

    Conclusions:

    • Computationally optimized shade guide models with 4-6 tabs offer improved accuracy over traditional physical guides.
    • This biomimetic approach, based on an extensive in vivo database, can lead to better shade matching with fewer tabs.
    • The validated approach provides a foundation for future dental shade guide materials and systems.