Muon tomography is a novel method for the non-destructive imaging of materials based on muon rays,which are highly penetrating in natural background radia-tion.Currently,the most commonly used imaging methods include muon radiography and muon tomography.A pre-viously studied method known as coinciding muon trajec-tory density tomography,which utilizes muonic secondary particles,is proposed to image low and medium atomic number(Z)materials.However,scattering tomography is mostly used to image high-Z materials,and coinciding muon trajectory density tomography exhibits a hollow phenomenon in the imaging results owing to the self-ab-sorption effect.To address the shortcomings of the indi-vidual imaging methods,hybrid model tomography combining scattering tomography and coinciding muon trajectory density tomography is proposed and verified.In addition,the peak signal-to-noise ratio was introduced to quantitatively analyze the image quality.Different imaging models were simulated using the Geant4 toolkit to confirm the advantages of this innovative method.The simulation results showed that hybrid model tomography can image centimeter-scale materials with low,medium,and high Z simultaneously.For high-Z materials with similar atomic numbers,this method can clearly distinguish those with apparent differences in density.According to the peak signal-to-noise ratio of the analysis,the reconstructed image quality of the new method was significantly higher than that of the individual imaging methods.This study provides a reliable approach to the compatibility of scat-tering tomography and coinciding muon trajectory density tomography.

Si-Yuan Luo;Yu-He Huang;Xuan-Tao Ji;Lie He;Wan-Cheng Xiao;Feng-Jiao Luo;Song Feng;Min Xiao;Xiao-Dong Wang

School of Nuclear Science and Technology,University of South China,Hengyang 421001,China

核技术（英文版）

[1]Si-Yuan Luo;Yu-He Huang;Xuan-Tao Ji;Lie He;Wan-Cheng Xiao;Feng-Jiao Luo;Song Feng;Min Xiao;Xiao-Dong Wang-.Hybrid model for muon tomography and quantitative analysis of image quality)[J].核技术（英文版）,2022(07):1-13

muonic

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