Pilot Study of Image Sementation and Decision Making by Neural Network
| Project/Area Number |
01550333
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | Kyoto University |
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Principal Investigator |
EIHO Shigeru Kyoto University, Faculty of Engineering, Professor, 工学部, 教授 (40026117)
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| Co-Investigator(Kenkyū-buntansha) |
ASADA Naoki Okayama University, Faculty of Engineering, Assistant Professor, 工学部, 助教授 (10167885)
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| Project Period (FY) |
1989 – 1990
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| Project Status |
Completed (Fiscal Year 1990)
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| Budget Amount *help |
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 1990: ¥300,000 (Direct Cost: ¥300,000)
Fiscal Year 1989: ¥1,500,000 (Direct Cost: ¥1,500,000)
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| Keywords | Neural Network / RI Image / Image Recognition |
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| Research Abstract |
An Artificial neural network has been applied for pattern recognition and used as a tool in an expert system. The purpose of this study is to examine the potential usefulness of the neural network approach in medical applications for image recognition. Multilayer feedforward neural networks with a back-propagation algorithm is designed for this study. Using first-pass radionuclide venticulograms, we attempted to identify the right and left ventricles of the heart and the lungs by training the neural network from patterns of time-activity curves. In a preliminary study, the neural network enabled identification of the lungs and heart chambers once the network was trained sufficiently by means of repeated entries of data from the same case. Thus neural networks can assist in solving complex problem in the medical field because they can recognize and discriminate certain patterns after training with many examples.
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Report
(3 results)
Research Products
(7 results)
