Uniformity and homogeneity issues with concurrent iterative reconstruction algorithms

Concurrent iterative reconstruction algorithms are iterative reconstruction algorithms that inject projection data into 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. Depending on the requirements of the final clinical application, the algorithms can offer a reduction in post-acquisition reconstruction time when compared to conventional iterative algorithms and provide images free of reconstruction inhomogeneities.