Dental Numbering for Periapical Radiograph Based on Multiple Fuzzy Attribute Approach
Author(s) -
Martin Leonard Tangel,
Chastine Fatichah,
Fei Yan,
Janet Pomares Betancourt,
M. Rahmat Widyanto,
Fangyan Dong,
Kaoru Hirota
Publication year - 2014
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2014.p0253
Subject(s) - numbering , radiography , computer science , dentistry , panoramic radiograph , identification (biology) , orthodontics , artificial intelligence , medicine , algorithm , radiology , botany , biology
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.
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