Maximum likelihood estimation

which is classical in PET reconstruction

is of statistically optimal solution.However

with the increasing of the iterations

the noise's influence on the reconstruction of the image increases.MAP(maximum a posteriori) reconstruction algorithm was studied.The negative effect of MAP such as over-smoothing caused by inappropriate constraints was analyzed.A new Bayesian reconstruction algorithm based on fuzzy theory was proposed to enhance the noise performance and to preserve the edge information.The fuzzy weight average filter and median filter were used in the algorithm.Simulations showed that the proposed method not only performed well for noise suppression

but also preferably kept the edges of the reconstruction image.