SPATIAL HOMOGENEITY ISSUES WITH CONCURRENT ITERATIVE RECONSTRUCTION ALGORITHMS

Concurrent Iterative Reconstruction Algorithms use projection data in the iterative process as the data become available during the SPECT ac quisition process and continue iterations in the post-acquisition peri od as conventional iterative algorithms. Because projections acquired early are processed more than later projections, regional inhomogeneit ies may exist in the initial image estimates but decrease with further post-acquisition iteration. Regularization done either during the acq uisition or post-acquisition iterations further reduces regional inhom ogeneities. We tested statistical differences in regions throughout th e reconstructed image to determine the minimal number of post-acquisit ion iterations and type of regularization needed to reach an image tha t is inter-regionally consistent. The algorithms provide images free o f reconstruction inhomogeneities and can offer a reduction in post-acq uisition reconstruction time when compared to conventional iterative a lgorithms.