Image oscillation reduction and convergence acceleration for OS-EM reconstruction

We have investigated the use of two approaches to reduce the image oscillation of OS-EM reconstruction that is due to the inconsistent adjustments from different partial subsets of the projection measurements (sinogram). One approach preprocesses the sinogram to make it satisfy a sinogram consistency condition. The second approach takes the average of the intermediary images (i.e., smoothes image values over sub-iterations). Both approaches were found to be capable of reducing the image oscillation, and combination of both was most effective. With these approaches, the convergence speed of the OS-EM is further improved. For computer simulated data and real PET data, a single iteration of these new OS-EM reconstruction was shown to yield images comparable to those with 80 EM iterations