Investigating four algorithms for material discrimination in a simulated dual-energy radiography system

The objective of this article is to enhance a method for effectively discriminating light metallic materials from heavy ones at low X-ray energies. In this research, Monte Carlo simulations are employed to investigate the influential factors affecting material discrimination. Initially, for result validation, the experimental setup is fully simulated based on Monte Carlo method. The X-ray spectrum of 160 keV is simulated and then it is registered after interacting with step wedges made of iron, aluminum, graphite, and ABS at specific thicknesses, capturing the radiation flux at each step. The results are compared with the experimental findings obtained from a dual-layer detector, demonstrating excellent agreement. In practice, the dual-layer detector comprises a low-energy GOS detector, a copper filter, and a high-energy CsI(Tl) detector. The energy spectra of the registered X-rays on each layer of detectors are obtained using the Monte Carlo method. Materials with low, medium, and high atomic numbers are chosen for analysis. These materials are categorized into three groups: organic materials (comprising both light and heavy organic and biological substances), light metals, and heavy metals. Discrimination between materials is achieved independently of their thickness by utilizing a Material Classification Map (MCM) derived from a graph depicting the transmission ratio of low-energy X-ray photons versus the linear attenuation coefficient ratio for various materials with different atomic numbers. The results have been successfully validated through testing with various materials and thicknesses using both the experimental setup and Monte Carlo simulations.

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Classification of Electronic Waste Components through X-ray and Neutron-Based Imaging Techniques

Buczkó,

Papp,

Maróti

et al. 2024

Materials

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In modern society, the amount of e-waste is growing year by year. Waste electronic items are complex, highly heterogeneous systems, containing organic material as well as several exotic, valuable, toxic, mostly metallic elements. In this study, the potential of X-ray and neutron radiography to reveal the inner structure of various complex e-waste was investigated. The images obtained using the two techniques were evaluated together to investigate the possibility of a more efficient segmentation of the individual components. The advantages and limitations of the two methods were identified for the studied waste types. X-ray radiography was found to be preferable for the identification of small metallic parts and for revealing the internal structure of e-waste with thick plastic coatings. Neutron radiography allowed for the identification of several components that did not provide sufficient contrast with X-ray imaging due to their similar X-ray attenuation compared to their surroundings. The combination of the two methods opens up new opportunities and could provide much more effective segmentation than either method alone.

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Investigating four algorithms for material discrimination in a simulated dual-energy radiography system

Cited by 3 publications

References 19 publications

Impact of object positioning and Compton scattering on material discrimination in high-energy X-ray cargo scans

Impact of object positioning and Compton scattering on material discrimination in high-energy X-ray cargo scans

Material Classification Map Using Dual-Energy Method at Low-Energy X-Ray Spectrum: An Experimental and Monte Carlo Simulation Study

Classification of Electronic Waste Components through X-ray and Neutron-Based Imaging Techniques

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