The Maximum Likelihood-Expectation Maximization (ML-EM) method was applied to 3D image reconstruction of cosmic-ray muon tomography. The feasibility was examined by using Monte Carlo simulation for a simple configuration where two lead blocks were placed at a different height from a muography detector. The 2D projection of the average thickness of the blocks as a function of the muon direction was simulated for multiple detection positions. The 3D image of the density profile was reconstructed by applying the ML-EM method to the simulated projections. It was found that the image reproduces reasonably well the position of the two blocks. The effect of the limited number of detection positions and the number of iteration in the ML-EM method on the image reconstruction was investigated in detail.

A feasibility demonstration of three-dimensional (3D) muon tomography was performed for infrastructure equivalent targets using the proposed portable muography detector. For the target, we used two sets of lead blocks placed at different heights. The detector consists of two muon position-sensitive detectors, made of plastic scintillating fibers (PSFs) and multi-pixel photon counters (MPPCs) with an angular resolution of 8 msr. In this work, the maximum likelihood-expectation maximization (ML-EM) method was used for the 3D imaging reconstruction of the muography. For both simulation and experiment, the reconstructed positions of the blocks produce consistent results with prior knowledge of the blocks' arrangement. This result demonstrates the potential of the 3D tomographic imaging of infrastructure by using seven detection positions for portable muography detectors to image infrastructure scale targets.

No abstract