| Project/Area Number |
17K15868
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Medical and hospital managemen
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| Research Institution | Hokkaido University of Science |
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Principal Investigator |
Yagahara Ayako 北海道科学大学, 保健医療学部, 講師 (50711884)
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| Project Period (FY) |
2017-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 自然言語処理 / 固有表現抽出 / オントロジー / 放射線検査 / 画像診断 / コンピュータ支援診断システム / 形態素解析 / コンピュータ支援診断 |
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| Outline of Final Research Achievements |
Computer-Aided Diagnosis (CAD) systems have gained attention as essential support for a clinical decision of “particular” diseases. The purpose of this study was to construct an integrating imaging diagnosis system focusing on a wide variety of diseases. This system combines the lesion detection by CAD with a diagnostic imaging ontology. uring this research period, three following ontologies were constructed: normal imaging anatomy, relations between diseases and image findings, and relations between image findings and image analysis. The integration of these three ontologies will not only be the foundation of a CAD that contributes to the detection of a wide variety of diseases but will be an explainable artificial intelligence.
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| Academic Significance and Societal Importance of the Research Achievements |
本オントロジーは、画像データから得られる特徴量を抽出し、その出現パターンや濃度勾配等を既知の医学知見と照合し、医学的事象の判断能力の獲得を目指している。これは、人工知能技術による医療者の思考と類似した処理の実現である。本研究で構築したオントロジーは幅広い疾患に対応するCADシステムの基盤となるとともに、処理過程が明確となるため、説明可能な人工知能システムの開発にもつながると考えている。
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