Sparse-view neutron CT 3D image reconstruction algorithm based on split Bregman method

IF 3.6 1区 物理与天体物理 Q1 NUCLEAR SCIENCE & TECHNOLOGY
Teng-Fei Zhu, Yang Liu, Zhi Luo, Xiao-Ping Ouyang
{"title":"Sparse-view neutron CT 3D image reconstruction algorithm based on split Bregman method","authors":"Teng-Fei Zhu, Yang Liu, Zhi Luo, Xiao-Ping Ouyang","doi":"10.1007/s41365-024-01439-9","DOIUrl":null,"url":null,"abstract":"<p>As a complement to X-ray computed tomography (CT), neutron tomography has been extensively used in nuclear engineering, materials science, cultural heritage, and industrial applications. Reconstruction of the attenuation matrix for neutron tomography with a traditional analytical algorithm requires hundreds of projection views in the range of 0° to 180° and typically takes several hours to complete. Such a low time-resolved resolution degrades the quality of neutron imaging. Decreasing the number of projection acquisitions is an important approach to improve the time resolution of images; however, this requires efficient reconstruction algorithms. Therefore, sparse-view reconstruction algorithms in neutron tomography need to be investigated. In this study, we investigated the three-dimensional reconstruction algorithm for sparse-view neutron CT scans. To enhance the reconstructed image quality of neutron CT, we propose an algorithm that uses OS-SART to reconstruct images and a split Bregman to solve for the total variation (SBTV). A comparative analysis of the performances of each reconstruction algorithm was performed using simulated and actual experimental data. According to the analyzed results, OS-SART-SBTV is superior to the other algorithms in terms of denoising, suppressing artifacts, and preserving detailed structural information of images.</p>","PeriodicalId":19177,"journal":{"name":"Nuclear Science and Techniques","volume":"41 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nuclear Science and Techniques","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1007/s41365-024-01439-9","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

As a complement to X-ray computed tomography (CT), neutron tomography has been extensively used in nuclear engineering, materials science, cultural heritage, and industrial applications. Reconstruction of the attenuation matrix for neutron tomography with a traditional analytical algorithm requires hundreds of projection views in the range of 0° to 180° and typically takes several hours to complete. Such a low time-resolved resolution degrades the quality of neutron imaging. Decreasing the number of projection acquisitions is an important approach to improve the time resolution of images; however, this requires efficient reconstruction algorithms. Therefore, sparse-view reconstruction algorithms in neutron tomography need to be investigated. In this study, we investigated the three-dimensional reconstruction algorithm for sparse-view neutron CT scans. To enhance the reconstructed image quality of neutron CT, we propose an algorithm that uses OS-SART to reconstruct images and a split Bregman to solve for the total variation (SBTV). A comparative analysis of the performances of each reconstruction algorithm was performed using simulated and actual experimental data. According to the analyzed results, OS-SART-SBTV is superior to the other algorithms in terms of denoising, suppressing artifacts, and preserving detailed structural information of images.

Abstract Image

基于分裂布雷格曼方法的稀疏视图中子 CT 三维图像重建算法
作为 X 射线计算机断层扫描(CT)的补充,中子断层扫描已广泛应用于核工程、材料科学、文化遗产和工业领域。使用传统的分析算法重建中子断层成像的衰减矩阵需要数百个 0° 至 180° 范围内的投影视图,通常需要几个小时才能完成。如此低的时间分辨率会降低中子成像的质量。减少投影采集次数是提高图像时间分辨率的重要方法,但这需要高效的重建算法。因此,需要研究中子断层成像中的稀疏视图重建算法。在这项研究中,我们研究了稀疏视图中子 CT 扫描的三维重建算法。为了提高中子 CT 的重建图像质量,我们提出了一种使用 OS-SART 重建图像和分裂 Bregman 求解总变异(SBTV)的算法。我们利用模拟和实际实验数据对每种重建算法的性能进行了比较分析。根据分析结果,OS-SART-SBTV 在去噪、抑制伪影和保留图像的详细结构信息方面优于其他算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Nuclear Science and Techniques
Nuclear Science and Techniques 物理-核科学技术
CiteScore
5.10
自引率
39.30%
发文量
141
审稿时长
5 months
期刊介绍: Nuclear Science and Techniques (NST) reports scientific findings, technical advances and important results in the fields of nuclear science and techniques. The aim of this periodical is to stimulate cross-fertilization of knowledge among scientists and engineers working in the fields of nuclear research. Scope covers the following subjects: • Synchrotron radiation applications, beamline technology; • Accelerator, ray technology and applications; • Nuclear chemistry, radiochemistry, radiopharmaceuticals, nuclear medicine; • Nuclear electronics and instrumentation; • Nuclear physics and interdisciplinary research; • Nuclear energy science and engineering.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信