2022 Fiscal Year Final Research Report
Application of deep learning to abdominal diagnostic imaging
| Project/Area Number |
18K15542
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 52040:Radiological sciences-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Keywords | 深層学習 |
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| Outline of Final Research Achievements |
We applied deep learning technology to diagnostic imaging by developing models (a) which can stage liver fibrosis based on CT or MRI, (b) which can predict bone mineral density from CT image, and (c) which can identify esophageal cancer on CT. Then, we reported these study results as original articles in academic journals.
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| Free Research Field |
深層学習の画像診断への応用
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| Academic Significance and Societal Importance of the Research Achievements |
深層学習の放射線画像診断への応用を行い、様々なモデルを開発することができた。これらの深層学習モデルを用いることで、放射線画像診断医の診断能を向上したり、放射線画像診断による主観的な評価では得ることが困難であった情報を画像から引き出すことが可能となり、診療の質を向上させることが期待される。
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