Analysis of fuzzy segmented based reconstructed PET liver image using MLEM algorithm

This paper possess the fuzzy segmented based performance analysis for the reconstruction of a non linear PET Liver image using fuzzy logic controlled Maximum Likelihood Expectation Maximization (MLEM). The various types of iteration method used are MAP, MLEM and OSEM. MLEM, an iteration approach, has more advantage for reconstructing the Positron Emission Tomography (PET) when comparing with the analytical approach which requires a minimization of a convex cost function and accompanied by many problems related to the computational complexity. Knowledge based fuzzy controlled technique is used which provides better Average Difference value along with lowest noise in the PET Liver image thus improves the using of Maximum Likelihood Expectation Maximization (MLEM) algorithm. The PET liver image is constructed and simulated in MATLAB/Simulink package.