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3D robust anisotropic diffusion filtering algorithm for sparse view neutron computed tomography 3D image reconstruction

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Nuclear Science and Techniques 2024年第3期35卷 13-29页

作者： Yang Liu Teng-Fei Zhu Zhi Luo Xiao-Ping Ouyang School of Nuclear Science and Engineering North China Electric Power UniversityBeijing 102206China State Key Laboratory of Nuclear Resources and Environment East China University of TechnologyNanchang 330013China State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Xi’an 710024China

The most critical part of a neutron computed tomography(NCT) system is the image processing algorithm,which directly affects the quality and speed of the reconstructed *** types of noise in the system can degrade the quality of the reconstructed ***,to improve the quality of the reconstructed images of NCT systems,efficient image processing algorithms must be *** anisotropic diffusion filtering(ADF) algorithm can not only effectively suppress the noise in the projection data,but also preserve the image edge structure information by reducing the diffusion at the image ***,we propose the application of the ADF algorithm for NCT image *** compare the performance of different algorithms in NCT systems,we reconstructed images using the ordered subset simultaneous algebraic reconstruction technique(OS-SART) algorithm with different regular terms as image processing *** the iterative reconstruction,we selected two image processing algorithms,the Total Variation and split Bregman solved total variation algorithms,for comparison with the performance of the ADF ***,the filtered back-projection algorithm was used for comparison with an iterative *** reconstructing the projection data of the numerical and clock models,we compared and analyzed the effects of each algorithm applied in the NCT *** on the reconstruction results,OS-SART-ADF outperformed the other algorithms in terms of denoising,preserving the edge structure,and suppressing *** example,when the 3D Shepp–Logan was reconstructed at 25 views,the root mean square error of OS-SART-ADF was the smallest among the four iterative algorithms,at only *** universal quality index,mean structural similarity,and correlation coefficient of the reconstructed image were the largest among all algorithms,with values of 0.9877,0.9878,and 0.9887,respectively.

关键词： NCT OS-SART sparse-view Anisotropic diffusion filtering

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First-order primal-dual algorithm for sparse-view neutron computed tomography-based three-dimensional image reconstruction

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Nuclear Science and Techniques 2023年第8期34卷 35-53页

Neutron computed tomography(NCT)is widely used as a noninvasive measurement technique in nuclear engineering,thermal hydraulics,and cultural *** neutron source intensity of NCT is usually low and the scan time is long,resulting in a projection image containing severe *** reduce the scanning time and increase the image reconstruction quality,an effective reconstruction algorithm must be *** CT image reconstruction,the reconstruction algorithms can be divided into three categories:analytical algorithms,iterative algorithms,and deep *** the analytical algorithm requires complete projection data,it is not suitable for reconstruction in harsh environments,such as strong radia-tion,high temperature,and high *** learning requires large amounts of data and complex models,which cannot be easily deployed,as well as has a high computational complexity and poor ***,this paper proposes the OS-SART-PDTV iterative algorithm,which uses the ordered subset simultaneous algebraic reconstruction technique(OS-SART)algorithm to reconstruct the image and the first-order primal–dual algorithm to solve the total variation(PDTV),for sparse-view NCT three-dimensional *** novel algorithm was compared with other algorithms(FBP,OS-SART-TV,OS-SART-AwTV,and OS-SART-FGPTV)by simulating the experimental data and actual neutron projection *** reconstruction results demonstrate that the proposed algorithm outperforms the FBP,OS-SART-TV,OS-SART-AwTV,and OS-SART-FGPTV algorithms in terms of preserving edge structure,denoising,and suppressing artifacts.

关键词： NCT First-order primal-dual algorithm OS-SART Total variation sparse-view

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维普期刊数据库

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Hybrid reconstruction algorithm for computed tomography based on diagonal total variation

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Nuclear Science and Techniques 2018年第3期29卷 172-180页

作者： Lu-Zhen Deng Peng He Shang-Hai Jiang Mian-Yi Chen Biao Wei Peng Feng Key Laboratory of Optoelectronic Technology and Systems Ministry of Education Chongqing University Department of Radiation Physics The University of Texas MD Anderson Cancer Center ICT NDT Engineering Research Center Ministry of Education Chongqing University Collaborative Innovation Center for Brain Science Chongqing University

Inspired by total variation(TV), this paper represents a new iterative algorithm based on diagonal total variation(DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reconstructed image, we used DTV to sparsely represent images when iterative convergence of the reconstructed algorithm with TV-constraint had no effect during the reconstruction process. To investigate our proposed algorithm, the numerical and experimental studies were performed, and rootmean-square error(RMSE) and structure similarity(SSIM)were used to evaluate the reconstructed image quality. The results demonstrated that the proposed method could effectively reduce noise, suppress artifacts, and reconstruct highquality image from incomplete projection data.

关键词： Computed tomography (CT) sparse-view reconstruction Diagonal total variation (DTV) Compressive sensing (CS)

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