用于 PET 双能 CT 成像的 γ 射线 CT 图像超分辨率重建。

IF 2.3 3区 生物学 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Genome Pub Date : 2024-02-01 Epub Date: 2023-04-07 DOI:10.1117/12.2654431
Yansong Zhu, Benjamin A Spencer, Zhaoheng Xie, Edwin K Leung, Reimund Bayerlein, Negar Omidvari, Simon R Cherry, Jinyi Qi, Ramsey D Badawi, Guobao Wang
{"title":"用于 PET 双能 CT 成像的 γ 射线 CT 图像超分辨率重建。","authors":"Yansong Zhu, Benjamin A Spencer, Zhaoheng Xie, Edwin K Leung, Reimund Bayerlein, Negar Omidvari, Simon R Cherry, Jinyi Qi, Ramsey D Badawi, Guobao Wang","doi":"10.1117/12.2654431","DOIUrl":null,"url":null,"abstract":"<p><p>Dual-energy computed tomography (DECT) enables material decomposition for tissues and produces additional information for PET/CT imaging to potentially improve the characterization of diseases. PET-enabled DECT (PDECT) allows the generation of PET and DECT images simultaneously with a conventional PET/CT scanner without the need for a second x-ray CT scan. In PDECT, high-energy <math><mstyle><mi>γ</mi></mstyle></math>-ray CT (GCT) images at 511 keV are obtained from time-of-flight (TOF) PET data and are combined with the existing x-ray CT images to form DECT imaging. We have developed a kernel-based maximum-likelihood attenuation and activity (MLAA) method that uses x-ray CT images as a priori information for noise suppression. However, our previous studies focused on GCT image reconstruction at the PET image resolution which is coarser than the image resolution of the x-ray CT. In this work, we explored the feasibility of generating super-resolution GCT images at the corresponding CT resolution. The study was conducted using both phantom and patient scans acquired with the uEXPLORER total-body PET/CT system. GCT images at the PET resolution with a pixel size of 4.0 mm × 4.0 mm and at the CT resolution with a pixel size of 1.2 mm × 1.2 mm were reconstructed using both the standard MLAA and kernel MLAA methods. The results indicated that the GCT images at the CT resolution had sharper edges and revealed more structural details compared to the images reconstructed at the PET resolution. Furthermore, images from the kernel MLAA method showed substantially improved image quality compared to those obtained with the standard MLAA method.</p>","PeriodicalId":12809,"journal":{"name":"Genome","volume":"32 1","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10947795/pdf/","citationCount":"0","resultStr":"{\"title\":\"<ArticleTitle xmlns:ns0=\\\"http://www.w3.org/1998/Math/MathML\\\">Super-resolution reconstruction of <ns0:math><ns0:mstyle><ns0:mstyle><ns0:mi>γ</ns0:mi></ns0:mstyle></ns0:mstyle></ns0:math>-ray CT images for PET-enabled dual-energy CT imaging.\",\"authors\":\"Yansong Zhu, Benjamin A Spencer, Zhaoheng Xie, Edwin K Leung, Reimund Bayerlein, Negar Omidvari, Simon R Cherry, Jinyi Qi, Ramsey D Badawi, Guobao Wang\",\"doi\":\"10.1117/12.2654431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Dual-energy computed tomography (DECT) enables material decomposition for tissues and produces additional information for PET/CT imaging to potentially improve the characterization of diseases. PET-enabled DECT (PDECT) allows the generation of PET and DECT images simultaneously with a conventional PET/CT scanner without the need for a second x-ray CT scan. In PDECT, high-energy <math><mstyle><mi>γ</mi></mstyle></math>-ray CT (GCT) images at 511 keV are obtained from time-of-flight (TOF) PET data and are combined with the existing x-ray CT images to form DECT imaging. We have developed a kernel-based maximum-likelihood attenuation and activity (MLAA) method that uses x-ray CT images as a priori information for noise suppression. However, our previous studies focused on GCT image reconstruction at the PET image resolution which is coarser than the image resolution of the x-ray CT. In this work, we explored the feasibility of generating super-resolution GCT images at the corresponding CT resolution. The study was conducted using both phantom and patient scans acquired with the uEXPLORER total-body PET/CT system. GCT images at the PET resolution with a pixel size of 4.0 mm × 4.0 mm and at the CT resolution with a pixel size of 1.2 mm × 1.2 mm were reconstructed using both the standard MLAA and kernel MLAA methods. The results indicated that the GCT images at the CT resolution had sharper edges and revealed more structural details compared to the images reconstructed at the PET resolution. Furthermore, images from the kernel MLAA method showed substantially improved image quality compared to those obtained with the standard MLAA method.</p>\",\"PeriodicalId\":12809,\"journal\":{\"name\":\"Genome\",\"volume\":\"32 1\",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10947795/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2654431\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/4/7 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1117/12.2654431","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/4/7 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

双能计算机断层扫描(DECT)可对组织进行物质分解,并为 PET/CT 成像提供额外信息,从而改善疾病的特征描述。PET-enabled DECT(PDECT)允许使用传统 PET/CT 扫描仪同时生成 PET 和 DECT 图像,而无需进行第二次 X 射线 CT 扫描。在 PDECT 中,511 千伏的高能 γ 射线 CT(GCT)图像由飞行时间(TOF)PET 数据获得,并与现有的 X 射线 CT 图像结合形成 DECT 成像。我们开发了一种基于核的最大似然衰减和活动(MLAA)方法,该方法使用 X 射线 CT 图像作为抑制噪声的先验信息。然而,我们之前的研究侧重于 PET 图像分辨率下的 GCT 图像重建,而 PET 图像分辨率比 X 射线 CT 图像分辨率更粗糙。在这项工作中,我们探索了以相应的 CT 分辨率生成超分辨率 GCT 图像的可行性。研究使用 uEXPLORER 全身 PET/CT 系统采集的模型和患者扫描进行。使用标准 MLAA 和核 MLAA 方法分别重建了 PET 分辨率下像素尺寸为 4.0 mm × 4.0 mm 和 CT 分辨率下像素尺寸为 1.2 mm × 1.2 mm 的 GCT 图像。结果表明,与 PET 分辨率下重建的图像相比,CT 分辨率下的 GCT 图像边缘更清晰,显示的结构细节更多。此外,与使用标准 MLAA 方法获得的图像相比,使用核 MLAA 方法获得的图像显示出更高的图像质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Super-resolution reconstruction of γ-ray CT images for PET-enabled dual-energy CT imaging.

Dual-energy computed tomography (DECT) enables material decomposition for tissues and produces additional information for PET/CT imaging to potentially improve the characterization of diseases. PET-enabled DECT (PDECT) allows the generation of PET and DECT images simultaneously with a conventional PET/CT scanner without the need for a second x-ray CT scan. In PDECT, high-energy γ-ray CT (GCT) images at 511 keV are obtained from time-of-flight (TOF) PET data and are combined with the existing x-ray CT images to form DECT imaging. We have developed a kernel-based maximum-likelihood attenuation and activity (MLAA) method that uses x-ray CT images as a priori information for noise suppression. However, our previous studies focused on GCT image reconstruction at the PET image resolution which is coarser than the image resolution of the x-ray CT. In this work, we explored the feasibility of generating super-resolution GCT images at the corresponding CT resolution. The study was conducted using both phantom and patient scans acquired with the uEXPLORER total-body PET/CT system. GCT images at the PET resolution with a pixel size of 4.0 mm × 4.0 mm and at the CT resolution with a pixel size of 1.2 mm × 1.2 mm were reconstructed using both the standard MLAA and kernel MLAA methods. The results indicated that the GCT images at the CT resolution had sharper edges and revealed more structural details compared to the images reconstructed at the PET resolution. Furthermore, images from the kernel MLAA method showed substantially improved image quality compared to those obtained with the standard MLAA method.

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
Genome
Genome 生物-生物工程与应用微生物
CiteScore
5.30
自引率
3.20%
发文量
42
审稿时长
6-12 weeks
期刊介绍: Genome is a monthly journal, established in 1959, that publishes original research articles, reviews, mini-reviews, current opinions, and commentaries. Areas of interest include general genetics and genomics, cytogenetics, molecular and evolutionary genetics, developmental genetics, population genetics, phylogenomics, molecular identification, as well as emerging areas such as ecological, comparative, and functional genomics.
×
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