| Project/Area Number |
26462679
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Ophthalmology
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Asaoka Ryo 東京大学, 医学部附属病院, 特任講師 (00362202)
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| Research Collaborator |
MURATA HIROSHI 東京大学, 医学部附属病院, 助教 (80635748)
FUJINO YURI 東京大学, 医学部附属病院, 特任研究員 (20768254)
MATSUURA MASATO 東京大学, 医学部附属病院, 特任研究員 (00768351)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2016: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2014: ¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
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| Keywords | 緑内障 / 視野進行予測 / 視野測定 |
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| Outline of Final Research Achievements |
A database of glaucomatous visual field was developed with 1348 eyes from 10 institutes in Japan. Using this database, it was suggested it was useful to regress visual field result against intraocular pressure integrated time rather than regressing against time. Also, it was suggested it was usefl to use deep learning method to detect early glaucomatous visual field change. It was suggested it was useful to combine these approaches with the variational Bayes linear regression, and the development of visual field measurement algorithm using these outcomes is on-going.
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