The Study of Cosmic Ray Tomography Using Multiple Scattering of Muons for Imaging of High-Z Materials

TL;DR

This paper demonstrates that the MLS-EM algorithm significantly improves the quality and efficiency of muon tomography imaging for detecting high-Z materials, with potential applications in homeland security.

Contribution

It introduces the use of the MLS-EM iterative algorithm for muon tomography, showing enhanced image quality and discrimination capabilities over the PoCA method.

Findings

MLS-EM outperforms PoCA in image quality and noise reduction

MLS-EM effectively discriminates high-Z materials in simulated scenarios

Parallel implementation of MLS-EM improves reconstruction speed

Abstract

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.