An improved OSEM(ordered subset expectation maximization) reconstruction algorithm with OR(overrelaxation) parameter is studied in order to provide a more rapid and practical convergent iterative reconstruction algorithm in tomograph of nuclear medicine

such as SPECT(single photon emission computed tomograph) and PET(positron emission tomograph). Based on the additive version of OSEM

the new method introduces a constant overrelaxation parameter z>1 during each sub-iteration

and imposes the non-negativity constrain and total-counts normalization condition in subset iteration to overcome the negative image value problem and total-counts shift

in order to ensure its rapid and stable convergence. The method is reduced into ordinary OSEM when z=1. The reconstructed images were compared with those of standard OSEM

by both simulated phantom data and clinical SPECT myocardial perfusion data. The OR-OSEM is shown to be one time faster than OSEM's with same subset level

and is even faster than the OSEM with higher subset level. The results also show that this OR-OSEM method is more flexible in practice due to its continuous adjustable OR parameter.