Based On Source Of Gamma Camera Image Three-dimensional Distribution Reconfiguration Technology Research

As the development of the nuclear industry, the nuclear facilities and radioactive sources have vigorous application in nuclear power, radio medicine, military science, aviation and cosmonautics, and so on. While the nuclear industry brings us considerable economic and social benefit, we must minimize the harm to the environment caused by the radioactivity. Recently, parts of the old nuclear facilities are already out of commission and more are facing with this problem in the coming decades, because many new nuclear facilities are being built in succession to substitute the old ones. Thus study of the technology of radiological characterization related with nuclear facilities out of commission is necessary and pressing.The emphases in the process of the source item investigation are estimating the retention and residual quantity, determining the type of contamination nuclides and the border of contaminated areas, and so on. Device of γ-ray radiation imaging, so-called y camera, is an imaging equipment that can gain the information about the positional distribution of radioactive source and distribution of radiation dose in contaminated area quickly, from a relatively long distance, and most directly, γ camera has been used in decontamination of nuclear facilities out of commission, radiation protection, evaluation of screening utility, response to the nuclear emergency, classified measurement of the nuclear waste, environmental protection and territorial security, etc.Acquiring3D radioactive distribution is one of the key technics to obtain accurate absolute detector efficiency which in turn enables more precise hold up measurement by γ spectrum approach. In order to estimate the retention and residual quantity, it has to know the three-dimensional distribution of the radioactive source. But the y camera can only obtain the two-dimensional image. So it will be very meaningful to reconstruct the three-dimensional distribution of the radioactive source according to the two-dimensional image obtained from the y camera.On the basis of research on γ camera imaging principle, an approach to reconstruct radioactive3D distribution from2D γ camera images was proposed. Statistical reconstruction method from medical CT reconstruction methods was chose from various3D imaging means as the measure to reconstruct radioactive3D distribution. The whole process was divided into two parts:restore γ images to perfect pinhole condition and then using restored image to reconstruct3D distribution, or namely, image restoration and image reconstruction. Richardson iterative restoration method was used as restore algorithm while ML-EM statistical reconstruction algorithm was used to reconstruct3D distribution. Physical and mathematical models were then built and several applications were programed accordingly. Image restoration models include simulative and experimental point spread function (PSF) model and applications to support this part consist γ camera data reading, image rotation, image restoration and image visualizing applications. Models in image reconstruction were made up by parallel and pinhole reconstruction model in which utilized an extremely generalized scheme, which can have the most applicability in practical measurement, where images from different angles and different positions can be randomly allied to reconstruct final result. A3D distribution data format was defined followed by several applications’ programing:3D reconstructing,3D distribution data slice and direct3D visualizing applications. Many γ images were simulated after a γ camera model built up in Monte Carlo program and then used to test and debug established scheme and applications. The final step was using experimental images for reconstruction after the γ camera was calibrated and adjusted properly. According to reconstruction results on simulated and experimental images, proposed radioactive3D distribution reconstruction scheme worked well. It is possible to acquire accurate radioactive3D position and intensity distribution based on a few γ camera images using statistical reconstruction method.