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Method for Automated Selection of the Trabecular Area in Digital Periapical Radiographic Images Using Morphological

Enny Itje Sela1, Reza Pulungan2, Rini Widyaningrum3

  • 1Department of Informatics, University of Technology Yogyakarta, Yogyakarta, Indonesia.

Healthcare Informatics Research
|August 14, 2019
PubMed
Summary

This study introduces an automated method using morphological operations to identify trabecular bone in dental X-rays. The technique shows promising accuracy, closely matching expert dentist segmentations for improved diagnostic imaging.

Keywords:
Cancellous BoneDentistImage EnhancementRadiographyValidation Studies

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Area of Science:

  • Radiology
  • Medical Imaging
  • Dental Diagnostics

Background:

  • Accurate segmentation of trabecular bone in digital periapical radiographs is crucial for dental diagnostics.
  • Manual identification of trabecular bone areas can be time-consuming and subjective.

Purpose of the Study:

  • To develop and validate an automated method for selecting trabecular bone areas in digital periapical radiographic images.
  • To utilize a sequence of morphological operations for precise trabecular bone segmentation.

Main Methods:

  • The study employed 50 digital periapical radiographic images from women aged 36-58.
  • A three-stage method involving teeth detection, trabecular identification, and validation was implemented.
  • Key morphological operations included top-hat/bottom-hat filtering, automatic and global thresholding, closing, labeling, and image subtraction.

Main Results:

  • The automated method successfully segmented trabecular bone areas, producing polygonal shapes.
  • The method's results showed an average agreement of 75.22% with dentists' manual segmentations.
  • The automated trabecular area was, on average, 5.83% smaller than dentists' identified areas, with a 8.75% disagreement.

Conclusions:

  • The proposed method generates trabecular bone shapes that are similar and closer to those identified by dental experts.
  • The technique, relying on simple morphological operations, offers an effective automated solution for trabecular bone area selection in dental radiography.