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 acquisition process and continue iterations in the post-acquisition period as conventional iterative algorithms. Because projections acquired early are processed more than later projections, regional inhomogeneities may exist in the initial image estimates but decrease with further post-acquisition iteration. Regularization done either during the acquisition or post-acquisition iterations further reduces regional inhomogeneities. The authors tested statistical differences in regions throughout the reconstructed image to determine the minimal number of post-acquisition iterations and type of regularization needed to reach an image that is inter-regionally consistent. The algorithms provide images free of reconstruction inhomogeneities and can offer a reduction in post-acquisition reconstruction time when compared to conventional iterative algorithms.