Motion correction of multi-frame PET data

In the context of motion correction of multi-frame PET data, we first conducted investigations which aimed at optimizing the parameters of a coregistration method, such as the choice of the target volume and the similarity criterion. The results indicate that the method providing the best motion recovery and introducing the lowest level of motions on undisplaced frames consists in reconstructing each PET frame with no correction and registering them with the time-average PET volume by maximizing the cross-correlation criterion. Based on these results we designed an optimal frame realignment method whose features and validation results are reported here. Preliminary clinical results are also given here.