Dynamic simulation of FDG-PET image based on VHP datasets

The FDG-PET is an important imaging tool for early diagnosis and treatment of malignant tumor and functional disease. The main purpose of this work is to propose a method for simulation of dynamic FDG-PET images based on VHP datasets. First the tissue time-activity curves (TTAC) are simulated using compartment model with blood time-activity curve (BTAC), and then the noises of each voxel are estimated according to the activity countering and the scan duration. At last according to the obtained BTAC and TTACs, a set of corresponding values are assigned to the segmented VHP image together with the independent Gaussian noise respectively. Series dynamic FDG-PET images were simulated respectively for normal physiology and pathology. The results of this work may provide a novel simulation platform for the research of PET image processing.