Pet Radioactive Concentration And Kinetic Parameters Robust Reconstruction

PET (positron emission tomography) plays a significant part in the medical image science and emerges as one of the leading modalities in biomedical research and clinical diagnostic procedure. PET image reconstruction, including static and dynamic reconstructions which provide diverse information, is one part of the PET research. In this thesis, we analysis the problem in the PET reconstruction in order to improve the development and application of PET, the elements and contributions are as follows:1,In this paper, a new system model is proposed for the PET reconstruction, which has the main challenge of the quality of image and the speed of reconstruction, using point clouds representation. According to the density of the prior image, this method adopts the content-adaptive point clouds, which has greatly reduced the computation and maintained the vital information reconstruction. The experiments, including the simulated data and the real scanned data, prove this method that reduces the calculation time while preserving the image quality at the same level simultaneously.2,This paper deals with the dual estimation of the activity maps and kinetic parameters for dynamic PET imaging. It is important to find out the related information between the various frames of images, and the compartmental models describe the metabolism from physiology and pathology with the kinetic parameters reflecting the real-time biological metabolism. We propose a novel approach to joint-estimate the activity maps and kinetic parameters by using dual filter based on the state space framework, which greatly improve the noise processing and have the optional results. The computer simulation experiments, containing one ROI and mulit-ROIs, demonstrate more robust and more accurate performance of our method compared with other methods.