[一种基于双向流场引导投影补全的稀疏视图锥束CT重建算法]。

Q3 Medicine
Wenwei Li, Zerui Mao, Yongbo Wang, Zhaoying Bian, Jing Huang
{"title":"[一种基于双向流场引导投影补全的稀疏视图锥束CT重建算法]。","authors":"Wenwei Li, Zerui Mao, Yongbo Wang, Zhaoying Bian, Jing Huang","doi":"10.12122/j.issn.1673-4254.2025.02.21","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>We propose a sparse-view cone-beam CT reconstruction algorithm based on bidirectional flow field guided projection completion (BBC-Recon) to solve the ill-posed inverse problem in sparse-view cone-beam CT imaging.</p><p><strong>Methods: </strong>The BBC-Recon method consists of two main modules: the projection completion module and the image restoration module. Based on flow field estimation, the projection completion module, through the designed bidirectional and multi-scale correlators, fully calculates the correlation information and redundant information among projections to precisely guide the generation of bidirectional flow fields and missing frames, thus achieving high-precision completion of missing projections and obtaining pseudo complete projections. The image restoration module reconstructs the obtained pseudo complete projections and then refines the image to remove the residual artifacts and further improve the image quality.</p><p><strong>Results: </strong>The experimental results on the public datasets of Mayo Clinic and Guilin Medical University showed that in the case of a 4-fold sparse angle, compared with the suboptimal method, the BBC-Recon method increased the PSNR index by 1.80% and the SSIM index by 0.29%, and reduced the RMSE index by 4.12%; In the case of an 8-fold sparse angle, the BBC-Recon method increased the PSNR index by 1.43% and the SSIM index by 1.49%, and reduced the RMSE index by 0.77%.</p><p><strong>Conclusions: </strong>The BBC-Recon algorithm fully exploits the correlation information between projections to allow effective removal of streak artifacts while preserving image structure information, and demonstrates significant advantages in maintaining inter-slice consistency.</p>","PeriodicalId":18962,"journal":{"name":"南方医科大学学报杂志","volume":"45 2","pages":"395-408"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11875868/pdf/","citationCount":"0","resultStr":"{\"title\":\"[A sparse-view cone-beam CT reconstruction algorithm based on bidirectional flow field- guided projection completion].\",\"authors\":\"Wenwei Li, Zerui Mao, Yongbo Wang, Zhaoying Bian, Jing Huang\",\"doi\":\"10.12122/j.issn.1673-4254.2025.02.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>We propose a sparse-view cone-beam CT reconstruction algorithm based on bidirectional flow field guided projection completion (BBC-Recon) to solve the ill-posed inverse problem in sparse-view cone-beam CT imaging.</p><p><strong>Methods: </strong>The BBC-Recon method consists of two main modules: the projection completion module and the image restoration module. Based on flow field estimation, the projection completion module, through the designed bidirectional and multi-scale correlators, fully calculates the correlation information and redundant information among projections to precisely guide the generation of bidirectional flow fields and missing frames, thus achieving high-precision completion of missing projections and obtaining pseudo complete projections. The image restoration module reconstructs the obtained pseudo complete projections and then refines the image to remove the residual artifacts and further improve the image quality.</p><p><strong>Results: </strong>The experimental results on the public datasets of Mayo Clinic and Guilin Medical University showed that in the case of a 4-fold sparse angle, compared with the suboptimal method, the BBC-Recon method increased the PSNR index by 1.80% and the SSIM index by 0.29%, and reduced the RMSE index by 4.12%; In the case of an 8-fold sparse angle, the BBC-Recon method increased the PSNR index by 1.43% and the SSIM index by 1.49%, and reduced the RMSE index by 0.77%.</p><p><strong>Conclusions: </strong>The BBC-Recon algorithm fully exploits the correlation information between projections to allow effective removal of streak artifacts while preserving image structure information, and demonstrates significant advantages in maintaining inter-slice consistency.</p>\",\"PeriodicalId\":18962,\"journal\":{\"name\":\"南方医科大学学报杂志\",\"volume\":\"45 2\",\"pages\":\"395-408\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-02-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11875868/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"南方医科大学学报杂志\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12122/j.issn.1673-4254.2025.02.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"南方医科大学学报杂志","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12122/j.issn.1673-4254.2025.02.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

摘要

目的:提出一种基于双向流场引导投影补全(BBC-Recon)的稀疏视图锥束CT重建算法,解决稀疏视图锥束CT成像中的不适定逆问题。方法:BBC-Recon方法包括投影补全模块和图像恢复模块两个主要模块。投影补全模块在流场估计的基础上,通过设计的双向多尺度相关器,充分计算投影之间的相关信息和冗余信息,精确指导双向流场和缺失帧的生成,从而实现对缺失投影的高精度补全,获得伪完整投影。图像恢复模块对得到的伪完整投影进行重建,然后对图像进行细化,去除残留的伪影,进一步提高图像质量。结果:在梅奥诊所和桂林医科大学公共数据集上的实验结果表明,在4倍稀疏角情况下,与次优方法相比,BBC-Recon方法的PSNR指数提高了1.80%,SSIM指数提高了0.29%,RMSE指数降低了4.12%;在8倍稀疏角情况下,BBC-Recon方法使PSNR指数提高1.43%,SSIM指数提高1.49%,RMSE指数降低0.77%。结论:BBC-Recon算法充分利用投影间的相关信息,在保留图像结构信息的同时有效去除条纹伪影,在保持片间一致性方面具有显著优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[A sparse-view cone-beam CT reconstruction algorithm based on bidirectional flow field- guided projection completion].

Objectives: We propose a sparse-view cone-beam CT reconstruction algorithm based on bidirectional flow field guided projection completion (BBC-Recon) to solve the ill-posed inverse problem in sparse-view cone-beam CT imaging.

Methods: The BBC-Recon method consists of two main modules: the projection completion module and the image restoration module. Based on flow field estimation, the projection completion module, through the designed bidirectional and multi-scale correlators, fully calculates the correlation information and redundant information among projections to precisely guide the generation of bidirectional flow fields and missing frames, thus achieving high-precision completion of missing projections and obtaining pseudo complete projections. The image restoration module reconstructs the obtained pseudo complete projections and then refines the image to remove the residual artifacts and further improve the image quality.

Results: The experimental results on the public datasets of Mayo Clinic and Guilin Medical University showed that in the case of a 4-fold sparse angle, compared with the suboptimal method, the BBC-Recon method increased the PSNR index by 1.80% and the SSIM index by 0.29%, and reduced the RMSE index by 4.12%; In the case of an 8-fold sparse angle, the BBC-Recon method increased the PSNR index by 1.43% and the SSIM index by 1.49%, and reduced the RMSE index by 0.77%.

Conclusions: The BBC-Recon algorithm fully exploits the correlation information between projections to allow effective removal of streak artifacts while preserving image structure information, and demonstrates significant advantages in maintaining inter-slice consistency.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
南方医科大学学报杂志
南方医科大学学报杂志 Medicine-Medicine (all)
CiteScore
1.50
自引率
0.00%
发文量
208
期刊介绍:
×
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:604180095
Book学术官方微信