  Muon tomography is developing as a promising system to detect high-Z (atomic
number) material for ensuring homeland security. In the present work, three
kinds of spatial locations of materials which are made of aluminum, iron, lead
and uranium are simulated with GEANT4 codes, which are horizontal, diagonal and
vertical objects, respectively. Two statistical algorithms are used with MATLAB
software to reconstruct the image of detected objects, which are the Point of
Closet Approach (PoCA) and Maximum Likelihood Scattering-Expectation
Maximization iterative algorithm (MLS-EM), respectively. Two analysis methods
are used to evaluate the quality of reconstruction image, which are the
Receiver Operating Characteristic (ROC) and the localization ROC (LROC) curves,
respectively. The reconstructed results show that, compared with PoCA
algorithm, MLS-EM can achieve a better image quality in both edge preserving
and noise reduction. And according to the analysis of ROC (LROC) curves, it
shows that MLS-EM algorithm can discriminate and exclude the presence and
location of high-Z object with a high efficiency, which is more flexible with
an different EM algorithm employed than prior work. Furthermore the MLS-EM
iterative algorithm will be modified and ran in parallel executive way for
improving the reconstruction speed.
