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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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OCT-Based Periodontal Inspection Framework.

Yu-Chi Lai1, Chia-Hsing Chiu1, Zhong-Qi Cai1

  • 1Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan.

Sensors (Basel, Switzerland)
|December 18, 2019
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Summary
This summary is machine-generated.

This study introduces a non-invasive Optical Coherence Tomography (OCT) framework for periodontal inspection. It accurately measures the distance between the gumline and alveolar bone, aiding in early disease detection.

Keywords:
OCT based periodontal inspectordeep network identifierperiodontal examination

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Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Periodontology

Background:

  • Periodontal diagnosis relies on visualizing teeth, gingiva, and alveolar bone, but alveolar bone is not directly visible.
  • Traditional methods like probing cause pain, and X-rays are unsuitable for frequent inspections due to radiation concerns.

Purpose of the Study:

  • To develop an automatic, non-invasive periodontal inspection framework using gum-penetrating Optical Coherence Tomography (OCT).
  • To enable frequent, radiation-free periodontal assessments by accurately identifying key anatomical boundaries.

Main Methods:

  • Utilized gum-penetrative OCT to capture subsurface gingival tissue data.
  • Developed an automatic framework employing adjusted Snake segmentation and truncated direct logarithm for intensity quantization to identify gumline and alveolar bone boundaries.
  • Calculated the distance between the gumline and alveolar bone for diagnostic insights.

Main Results:

  • The framework successfully identified gingiva, teeth, and alveolar bone regions from OCT cross-sectional volumes.
  • Demonstrated accurate localization of the gumline and alveolar line in vivo.
  • Verified the efficacy of the chosen intensity quantization and boundary identification algorithms.

Conclusions:

  • The developed OCT-based framework offers a non-invasive, radiation-free alternative for frequent periodontal inspections.
  • The system accurately measures critical periodontal parameters, facilitating early diagnosis and monitoring.
  • This technology holds significant potential for improving routine dental examinations and patient care.