| Project/Area Number |
61550257
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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 |
計算機工学
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| Research Institution | TOKYO INSTITUTE OF TECHNOLOGY |
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Principal Investigator |
OGAWA Hidemitsu Tokyo Institute of Technology, Department of Computer Science,, 工学部, 教授 (50016630)
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| Co-Investigator(Kenkyū-buntansha) |
IMIYA Atsushi Kanazawa University, Department of Electrical and Computer Engineering, 工学部, 講師 (10176505)
KUMAZAWA Itsuo Tokyo Institute of Technology, Department of Computer Science, 工学部, 助手 (70186469)
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| Project Period (FY) |
1986 – 1987
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| Project Status |
Completed (Fiscal Year 1987)
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| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1987: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1986: ¥1,600,000 (Direct Cost: ¥1,600,000)
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| Keywords | Computerized Tomography / Image reconstruction / Image restoration / Analog coding / Series expansion method / Cone beam projection / Three dimensional image reconstruction / 不完全投影 / 画像複元 |
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| Research Abstract |
Computerized Tomography has had a profound impact on medical diagnosis techniques. In the future, increasing computational power will make it possible to reconstruct 3 dimensional images directly from efficiently collected projections. In this research project we developped a theoretical basis for this ultimate goal from the following viewpoints.
(1) What is the most efficient scanning (sampling) schema to collect projections? And what way of arrangement of the sampling points gives us enough imformation to estimate the image uniquely? How can we reconstruct the image from these sampled data?
(2) Even in such an efficient sampling schema, there will be some redundancy among the data. How can we use the redundancy to make the reconstruction method robust and stable against the noise.
In this project we have snswered above questions as follows.
(1) As the efficient acsnning schema, we used the cone beam scanning schema and derived the conditions for the samplings in this schema to be enough to determine the image uniquely. In addition we developped the reconstruction formula for samplings using a series expansion method in which the optimal arrangement of the sample points was analytically discussed.
(2) We developped projection filter which uesd the redundancy in data to cancel the noise without degrading the resolution of the image. Finally, as another way of making use of the redunfancy, we decelopped an impulsive noise canceling technique based on the idea of analog coding.
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