Attenuation and scatter correction of list-mode data driven iterative and analytic image reconstruction algorithms for rotating 3D PET systems

Image reconstruction directly from list-mode data requires different data c orrection techniques to standard projection-data based reconstruction, part icularly in the case of iterative reconstruction. Attenuation and scatter c orrection techniques have been developed for two list-mode data driven reco nstruction algorithms (FAIR-B (iterative) and Atrax (analytic/iterative)) r ecently proposed by the authors, and the results compared with two fast pro jection-data based algorithms (FORE+OSEM (iterative) and FORE+FBP (analytic )). List-mode data driven algorithms require event-by-event correction sche mes, or alternatively image space procedures, as no direct operations to th e completely sampled projection data set can be practically carried out. Th e methods developed in this work allow correction of list-mode data driven EM-ML type algorithms, such as FAIR, as well as analytic list-mode algorith ms. The correction schemes have been applied to simulated data from various activity and attenuating medium distributions for a rotating 3D PET system . Both list-mode algorithms show some improvements in noise-contrast behavi our compared to the projection-data based methods.