X-ray CT Metal Artifact Reduction Using Segmentation and TV Regularisation

IF 0.9 4区 材料科学 Q4 MATERIALS SCIENCE, CHARACTERIZATION & TESTING
A. Allag, A. Benammar, T. Benmerar, W. Djerir, R. Drai, T. Boutkedjirt
{"title":"X-ray CT Metal Artifact Reduction Using Segmentation and TV Regularisation","authors":"A. Allag,&nbsp;A. Benammar,&nbsp;T. Benmerar,&nbsp;W. Djerir,&nbsp;R. Drai,&nbsp;T. Boutkedjirt","doi":"10.1134/S1061830923600636","DOIUrl":null,"url":null,"abstract":"<p>Metal artifacts pose a significant challenge in computed tomography (CT) image reconstruction. In this work, we present an approach based on sinogram inpainting and segmentation of both trace and metal objects for metal artifact reduction (MAR). We employ region growing segmentation to extract the metal trace from the sinogram as well as the metal objects. A first-order method is utilized in the sinogram inpainting step. The artifacts are substantially reduced when we apply the segmentation on the metal objects image obtained from the metal trace. To demonstrate the effectiveness of our approach, we evaluate it on both simulated and real images. Our MAR technique yields visually acceptable results with a reduced impact of metallic artifacts on the reconstructed tomographic images.</p>","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Journal of Nondestructive Testing","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1134/S1061830923600636","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
引用次数: 0

Abstract

Metal artifacts pose a significant challenge in computed tomography (CT) image reconstruction. In this work, we present an approach based on sinogram inpainting and segmentation of both trace and metal objects for metal artifact reduction (MAR). We employ region growing segmentation to extract the metal trace from the sinogram as well as the metal objects. A first-order method is utilized in the sinogram inpainting step. The artifacts are substantially reduced when we apply the segmentation on the metal objects image obtained from the metal trace. To demonstrate the effectiveness of our approach, we evaluate it on both simulated and real images. Our MAR technique yields visually acceptable results with a reduced impact of metallic artifacts on the reconstructed tomographic images.

Abstract Image

Abstract Image

利用分割和电视正则化减少 X 射线 CT 金属伪影
摘要 金属伪影是计算机断层扫描(CT)图像重建中的一个重大挑战。在这项工作中,我们提出了一种基于正弦图内绘制以及痕迹和金属物体分割的方法,用于减少金属伪影(MAR)。我们采用区域生长分割法从正弦曲线中提取金属痕迹和金属物体。在正弦图涂色步骤中使用了一阶方法。当我们对从金属痕迹中获得的金属物体图像进行分割时,伪影会大大减少。为了证明我们方法的有效性,我们在模拟图像和真实图像上对其进行了评估。我们的 MAR 技术在视觉上产生了可接受的结果,减少了金属伪影对重建断层图像的影响。
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
Russian Journal of Nondestructive Testing
Russian Journal of Nondestructive Testing 工程技术-材料科学:表征与测试
CiteScore
1.60
自引率
44.40%
发文量
59
审稿时长
6-12 weeks
期刊介绍: Russian Journal of Nondestructive Testing, a translation of Defectoskopiya, is a publication of the Russian Academy of Sciences. This publication offers current Russian research on the theory and technology of nondestructive testing of materials and components. It describes laboratory and industrial investigations of devices and instrumentation and provides reviews of new equipment developed for series manufacture. Articles cover all physical methods of nondestructive testing, including magnetic and electrical; ultrasonic; X-ray and Y-ray; capillary; liquid (color luminescence), and radio (for materials of low conductivity).
×
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