Principle Study of Image Reconstruction Algorithms in Muon Tomography

TL;DR

This paper investigates the fundamental principles of image reconstruction algorithms in muon tomography, comparing various methods through simulations to enhance image quality and material discrimination.

Contribution

It provides a detailed analysis of reconstruction principles and compares popular algorithms, offering insights for future improvements in muon tomography imaging.

Findings

Comparison of algorithms shows varying image quality and discrimination capabilities.

Simulation results highlight strengths and weaknesses of different reconstruction methods.

Proposes ideas for future algorithm enhancements.

Abstract

Muon tomography is a relatively new method of radiography that utilizes muons from cosmic rays and their multiple Coulomb scattering property to distinguish materials. Researchers around the world have been developing various detection systems and image reconstruction algorithms for muon tomography applications, such as nuclear reactor monitoring and cargo inspection for contraband. This paper studies the principle in image reconstruction of muon tomography. Implementation and comparison of some popular algorithms with our simulation dataset will be presented as well as some ideas of future improvements for better image qualities and material discrimination performances.