Individual Differences in Cut-Out Areas of Oral Images in Oral Mucosal Disease Diagnosis Support System
Nanto Ozaki*, Taishi Ohtani**, Manabu Habu**, Kazuhiro Tominaga**, and Keiichi Horio***
*National Institute of Technology, Oshima College
1091-1 Oaza-Komatsu, Suo-Oshima-cho, Oshima-gun, Yamaguchi 742-2193, Japan
**Kyushu Dental University
2-6-1 Manazuru, Kokurakitaku, Kitakyushu, Fukuoka 803-8580, Japan
***School of Life Science and Systems Engineering, Kyushu Institute of Technology
2-4 Hibikino, Wakamatsu, Kitakyushu, Fukuoka 803-0135, Japan
Oral mucosal disease is likely to cause various disorders after treatment to occur in a domain called the oral cavity. Therefore, we are developing a diagnostic support system for early screening of oral mucosal disease. There is a problem of individual differences in the cut-out of the disease area from the original intraoral image in system development. In this study, we analyzed the relationships between cutout areas, extracted features and classification rates and investigated the relationship between individual differences. Therefore, we focused on how to eliminate the subjects. Group classification was then performed and identification was performed using an oral mucosal diagnosis support system with ensemble learning. The experimental results revealed relationships between the excision range, identification rate, and feature value.
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