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Muon tomographic visualization techniques try to reconstruct a 3D image asclose as possible to the real localization of the objects being probed.Statistical algorithms under test for the reconstruction of muon tomographicimages in the Muon Portal Project are here discussed. Autocorrelation analysisand clustering algorithms have been employed within the context of methodsbased on the Point Of Closest Approach (POCA) reconstruction tool. An iterativemethod based on the log-likelihood approach was also implemented. Relativemerits of all such methods are discussed, with reference to full Geant4simulations of different scenarios, incorporating medium and high-Z objectsinside a container.

Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector