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22 March 2016 Multi-gamma-source CT imaging system: a feasibility study with the Poisson noise
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This study was performed to test the feasibility of multi-gamma-source CT imaging system. Gamma-source CT employs radioisotopes that emit monochromatic energy gamma-rays. The advantages of gamma-source CT include its immunity to beam hardening artifacts, its capacity of quantitative CT imaging, and its higher performance in low contrast imaging compared to the conventional x-ray CT. Radioisotope should be shielded by use of a pin-hole collimator so as to make a fine focal spot. Due to its low gamma-ray flux in general, the reconstructed image from a single gamma-source CT would suffer from high noise in data. To address this problem, we proposed a multi-gamma source CT imaging system and developed an iterative image reconstruction algorithm accordingly in this work. Conventional imaging model assumes a single linear imaging system typically represented by Mf = g. In a multi-gamma-source CT system however, the inversion problem is not any more based on a single linear system since one cannot separate a detector pixel value into multiple ones that are corresponding to each rays from the sources. Instead, the imaging model can be constructed by a set of linear system models each of which assumes an estimated measurement g. Based on this model, the proposed algorithm has a weighting step which distributes each projection data into multiple estimated measurements. We used two gamma sources at various positions and with varying intensities in this numerical study to demonstrate its feasibility. Therefore, the measured projection data(g) is separated into each estimated projection data(g1, g2) in this study. The proposed imaging protocol is believed to contribute to both medical and industrial applications.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sunhee Wi and Seungryong Cho "Multi-gamma-source CT imaging system: a feasibility study with the Poisson noise", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97831U (22 March 2016);

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