Development of an imaging algorithm for myocardial SPECT with a semiconductor detector
| Project/Area Number |
14570883
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Radiation science
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| Research Institution | Hosei University |
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Principal Investigator |
OGAWA Koichi Hosei University, Faculty of Engineering, Professor, 工学部, 教授 (00158817)
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| Project Period (FY) |
2002 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥3,400,000 (Direct Cost: ¥3,400,000)
Fiscal Year 2003: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2002: ¥2,500,000 (Direct Cost: ¥2,500,000)
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| Keywords | SPECT / Myocardial imaging / Data acquisition / Power spectrum / Image reconstruction |
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| Research Abstract |
The purpose of our research is to develop a new data acquisition scheme for myocardial single photon emission CT with a semiconductor detector. A gamma camera with a semiconductor detector enables us to measure projection data with arbitrary angles because the gamma camera with this detector is smaller than ordinary gamma cameras with a scintillation detector. The proposed data acquisition scheme is to measure projection data with angles where the signal to noise ratio in projection data is relatively high. We assumed that we could measure the heart with 25 projections. In the x-y plane the positions of the detector were φ=-30, 0, 30, 60 and 90 deg. and they were 0=30, 60, 90, 120 and 150 deg. to the z-axis. Then we decided the minimum number of projections required for an acceptable quality of images, and selected optimum projection angles. The criterion for selecting the projection angle was an integral value of the power spectrum for each projection. We listed projection data in descending order according to this integral value and made four projection subsets. A subset was composed of three projections, i.e., the projection which had the largest integral value and the other two projections which were perpendicular to the former one. In the image reconstruction we used the ordered subset expectation maximization method and used the above four subsets. As a result, even with only twelve projection data we could obtain images of almost the same quality as those obtained with 60 projections.
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Report
(3 results)
Research Products
(25 results)
