Dynamic performance improvement in computer-assisted detection system for diagnostic imaging by combined application of online learning and transfer learning
| Project/Area Number |
15K01325
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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 |
Medical systems
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Nomura Yukihiro 東京大学, 医学部附属病院, 特任研究員 (60436491)
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| Co-Investigator(Renkei-kenkyūsha) |
SATO Issei 東京大学, 大学院新領域創成科学研究科, 講師 (90610155)
MIKI Soichiro 東京大学, 医学部附属病院, 特任助教 (30707766)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | 医用画像 / 診断支援システム / 転移学習 / オンライン学習 / 画素識別処理 |
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| Outline of Final Research Achievements |
In this research, a dynamic performance improvement of computer-assisted (CAD) detection software by considering diversity of image data due to imaging scanner or imaging parameters was investigated. We constructed a training method of CAD software using online transfer learning algorithm, and verified by multicenter data. We also investigated whether a simplified method of gold standards definition can be used as an alternative to gold standards defined by pixel-by-pixel painting for CAD software using voxel-based classification.
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Report
(4 results)
Research Products
(7 results)
