  Point of colsest Approche algorithm (PoCA) based on the formalism of muon
radiogra- phy using Multiple Coulomb scattering (MCS) as information source is
previously used to obtain the reconstruction image of high Z material. The low
accuracy of reconstruction image is caused by two factors: the flux of natural
muon and the assumption of single scattering in PoCA algo- rithm. In this
paper, the maximum likelihood method based on the characteristics of
Gaussian-like distribution of muon tracks by MCS is used to predict the optimal
track of outgoing muon. The receiver operating characteristic (ROC) and the
localization ROC (LROC) are used as two analysis methods to evaluate the
quality of reconstruction image. From the results of simulation, the perfect
discrimination of longitudinal materials could be well achieved by maximum
likelihood algorithm and the discriminate ratio that is predicted by the
maximum likelihood method is about 15% higher than that of predicted by PoCA
algorithm method. It is seen that the maximum likelihood method can greatly
improve the accuracy of reconstruction image.
