| Project/Area Number |
17K18064
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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 systems
Biomedical engineering/Biomaterial science and engineering
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| Research Institution | Saitama Medical University |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2018: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 画像処理 / 病理画像 / 自家蛍光 / デジタル染色 / 深層学習 / 病理標本 / HE染色 / 位置合わせ / 画像認識 / 情報システム / 情報工学 |
|---|
| Outline of Final Research Achievements |
This study attempted to develop an unstained specimen digital staining method for use with autofluorescent images. After determining an autofluorescent image suitable for digital staining, the autofluorescent image and stain image were aligned and digital staining could be implemented using deep learning. However, the study also found that autofluorescence cannot be confirmed for some cell nuclei, proving that further technique improvements will be required in the future.
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| Academic Significance and Societal Importance of the Research Achievements |
未染色標本のデジタル染色が実現されれば，貴重な組織の染色が必要無くなる点や病理診断を行う際に，一つの組織で様々な染色が可能となることが期待される．これは病理診断の効率化や貴重な組織の保管など医学的意義が大きい．
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