Self normalization for continuous 3D whole body emission data in 3D PET

Continuous 3D scanning with a large-aperture PET scanner can provide high sensitivity over most of the axial FOV in whole-body studies. To minimum the artifact depended on the uniformity of the different lines-of-response (LORs) in sinograms, accurate normalizing algorithms will be needed. In this study, we propose self-normalization method in which full correction factors are derived from the emission data itself without using conventional normalize scan of cylinder phantom. In this method, transaxial block profile and crystal efficiency were calculated from the original emission data, and correction factors applied itself. We implemented proposed method to a 5 ring GSO PET scanner which has continuous 3D scan mode and evaluated. To accurate correction factor, components were calculated from dataset which summed in the direction of the bed movement. To investigate the performance, we compared the proposed method with conventional component based normalization using uniform cylinder phantom. And To evaluate clinical performance, we also ¹⁸FDG human studies were performed. In both phantom and human studies, the block profile and crystal efficiencies can be calculated correctly using proposed method. Evaluating percent standard deviation, self-normalization improved transaxial uniformity since it reduced ring artifacts. Especially, the accuracy of transaxial block profiles which influenced easily by some physical phenomena has unproved. Our self-normalize method was accurate enough for continuous 3D scanning with a large aperture PET scanner. The image quality using self-normalization was superior than conventional component normalization. This method contributes to the improvement of system operation , since regular acquisition of cylinder phantom for normalization is not necessary.