Dynamic PET image reconstruction with Geometrical structure
prior constraints
ZHANG Jun-chao1, YUE Mao-xiong2, LIU Hua-feng1
1. State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China;
2. The Fourth Research Institute,China Aerodynamics Research and Development Center, Mianyang 62100, China
In order to improve the image quality,an improved algorithm for dynamic positron emission tomography(PET) image reconstruction was proposed by using segmented anatomical template that provided by other high quality imaging technology. Based on state space theory, a dynamic PET image reconstruction framework for low count rate and high noise environment was formulated with the observation equation of detectors and a modified evolution equation incorporating structural constraint which was generated to guide the reconstruction process, and H∞ filtering principle was employed to solve the above two equations. Compared with other algorithms, experiments conducted by Monte Carlo simulations indicate a persuasive assessment that the proposed strategy was particularly applicable for real-world situations with the uncertainties of system and statistical properties, suppresses noise well, while the boundary information and other details remain clear.
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