DRAMA (Tanaka E, Kudo H, Phys Med Biol, 2003) provides fast convergence with a reasonable signal-to-noise ratio by updating the image with row-action by applying the subset-dependent relaxation parameter. A new method that automatically determines the next relaxation parameter based on the previous image update was proposed by Kudo in 2008. This method controls the relaxation parameter by monitoring the image convergence phase and is applicable to various conditions of the subset, access, and control unit of the relaxation parameter. In this study, we implemented this method on a whole-body 3D PET scanner (SET-3000G/X, Shimadzu Corporation) and investigated the optimal access order for subsets and the control unit of the relaxation parameter by comparing contrast-noise performance in NEMA IEC Body Phantom images. The performance obtained with DRAMA (one iteration) was significantly superior to that obtained with MLEM (multiple iterations). The optimal access order was the parallel sinogram first, followed by the remaining oblique sinograms in descending order. As for the control unit of the relaxation parameter, image convergence was expected to be faster with a smaller control unit, but its behavior was unstable due to statistical noise. The new method that controls the relaxation parameter in DRAMA was found to work well and to provide realistic 3D PET data. We will investigate the behavior of convergence values with various activity distribution conditions and statistical noise levels using clinical data in our future work.
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