2022 Fiscal Year Final Research Report
Development of tongue evaluation method using image recognition by deep learning
Project/Area Number |
20K18593
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 57050:Prosthodontics-related
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Research Institution | Niigata University |
Principal Investigator |
Okawa Jumpei 新潟大学, 医歯学系, 助教 (10846041)
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Project Period (FY) |
2020-04-01 – 2023-03-31
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Keywords | 舌苔 / 口腔乾燥 / Tongue Coating Index / 画像認識 / 深層学習 |
Outline of Final Research Achievements |
Tongue coating and tongue dryness may cause oral hypofunction, which can be evaluated from the tongue surface. However, a simple objective and detailed method for examining the status of tongue has not been established. Image recognition technology based on deep learning is applied to medical examinations. Therefore, we hypothesized that applying the Image recognition to photographs of the tongue could be applied to examinations for tongue. The tongue image of the older people was photographed, and the data of the tongue coating and the tongue dryness were obtained by dentists or examination equipment. Deep learning was performed to generate image recognition model to estimate the tongue status. The image recognition model could estimate the tongue coating status and the degree of tongue dryness.
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Free Research Field |
歯科補綴学
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Academic Significance and Societal Importance of the Research Achievements |
口腔機能の低下は、フレイルの主な原因である低栄養やサルコペニアを引き起こす。口腔衛生状態の不良による舌苔の付着や口腔乾燥による舌粘膜の湿潤度の低下は、口腔機能の低下を引き起こすことから、口腔機能低下症の診断基準の1つにもなっている。口腔機能が低下している者は、特に高齢者において在宅介護および施設入居、入院患者まで広く存在すると考えられる。 本研究より、舌の写真撮影から舌苔の付着や舌粘膜の湿潤度などの舌機能の評価が「だれでも・どこでも・簡単に」実施可能となる。さらに、評価に基づいた口腔ケアやリハビリ計画の決定に貢献できるものと考えている。
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