Dental numbering for periapical radiograph based on multiple fuzzy attribute approach

Martin Leonard Tangel, Chastine Fatichah, Fei Yan, Janet Pomares Betancourt, Muhammad RahmatWidyanto, Fangyan Dong, Kaoru Hirota

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The dental numbering for periapical radiograph based on multiple fuzzy attribute approach proposed here analyzes each individual tooth based on multiple criteria such as area/perimeter and width/height ratios. The classification and numbering in a special dental image called a periapical radiograph is studied without speculative classification in cases of ambiguous objects, so an accurate, assistive result is obtained due to the capability of handling ambiguous teeth. Experiment results in using periapical dental radiograph from the University of Indonesia indicate a total classification accuracy of 82.51%, an average classification rate per input radiograph of 84.29%, a maxilla-mandible identification accuracy from 78 radiographs of 82.05%, and a numbering accuracy from 15 radiographs of 90.47%. It is planned that the proposed classification and numbering be implemented as a submodule for dental-based personal identification now being developed.

Original languageEnglish
Pages (from-to)253-261
Number of pages9
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume18
Issue number3
DOIs
Publication statusPublished - May 2014

Keywords

  • Dental classification
  • Dental numbering
  • Fuzzy inference
  • Periapical radiograph
  • Personal identification

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