2020 Fiscal Year Final Research Report
Histological discrimination by Raman spectroscopy based on causal relationship
| Project/Area Number |
19K22969
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Review Section |
Medium-sized Section 90:Biomedical engineering and related fields
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| Research Institution | The University of Tokushima |
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Principal Investigator |
MINAMIKAWA Takeo 徳島大学, ポストLEDフォトニクス研究所, 准教授 (10637193)
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| Co-Investigator(Kenkyū-buntansha) |
安井 武史 徳島大学, ポストLEDフォトニクス研究所, 教授 (70314408)
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| Project Period (FY) |
2019-06-28 – 2021-03-31
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| Keywords | ラマン散乱分光法 / 末梢神経 / 神経温存手術 / 機械学習 |
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| Outline of Final Research Achievements |
In recent cancer surgery, not only the total resection of malignant legions but also the improvement of postoperative QOL of patients by peripheral nerve-sparing surgery is a crucial issue. This study proposed the selective detection method of peripheral nerves against adjacent tissues by utilizing the causal relationship of input data, spectral processing, and tissue discrimination results of Raman spectroscopy. Especially, we developed a machine learning optimization algorithm based on the evidence of tissue discrimination and clarified the features that are the basis of tissue discrimination.
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| Free Research Field |
顕微分光学
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| Academic Significance and Societal Importance of the Research Achievements |
従来の機械学習を用いた分光学的組織判別法では，入力データの処理層においてもはや人間には理解できない（物理的に理解ができない）情報処理が施されてしまっていた．そのため，情報処理の科学的根拠がわからないという点で，患者の命に関わる医療機器への適用には非常に高いリスクを伴う．本研究では，判別分析における因果関係に着目することで科学的根拠を明らかにしうる新たなラマン分光学的組織判別法を実現した点に学術的意義がある．本研究がさらに展開されることで，科学的根拠に基づく神経温存手術の実現が期待され，医学的意義を有する．
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