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

科研成果: 期刊稿件文章同行评审

4 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)253-261
页数9
期刊Journal of Advanced Computational Intelligence and Intelligent Informatics
18
3
DOI
出版状态已出版 - 5月 2014
已对外发布

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