AUTOMATED IMAGE REGISTRATION FOR FDOPA PET STUDIES

In this study, various image registration methods are investigated for their suitability for registration of L-6-[18F]-fluoro-DOPA (FDOPA) P ET images. Five different optimization criteria including sum of absol ute difference (SAD), mean square difference (MSD), crosscorrelation c oefficient (CC), standard deviation of pixel ratio (SDPR), and stochas tic sign change (SSC) were implemented and Powell's algorithm was used to optimize the criteria. The optimization criteria were calculated e ither unidirectionally (i.e. only evaluating the criteria for comparin g the resliced image 1 with the original image 2) or bidirectionally ( i.e. averaging the criteria for comparing the resliced image 1 with th e original image 2 and those for the sliced image 2 with the original image 1). Monkey FDOPA images taken at various known orientations were used to evaluate the accuracy of different methods. A set of human FD OPA dynamic images was used to investigate the ability of the methods for correcting subject movement. It was found that a large improvement in performance resulted when bidirectional rather than unidirectional criteria were used. Overall, the SAD, MSD and SDPR methods were found to be comparable in performance and were suitable for registering FDO PA images. The MSD method gave more adequate results for frame-to-fram e image registration for correcting subject movement during a dynamic FDOPA study. The utility of the registration method is further demonst rated by registering FDOPA images in monkeys before and after amphetam ine injection to reveal more clearly the changes in spatial distributi on of FDOPA due to the drug intervention.