Generalized series dynamic imaging

Zhi-Pei Liang
{"title":"Generalized series dynamic imaging","authors":"Zhi-Pei Liang","doi":"10.1109/MIAR.2001.930277","DOIUrl":null,"url":null,"abstract":"Many imaging applications require the acquisition of a time series of images. In conventional Fourier transform-based imaging methods, each of these images is acquired independently. As a result, the temporal resolution possible is limited by the number of data points collected for each data set, or one often was to sacrifice spatial resolution for temporal resolution. To overcome this problem, several \"data-sharing\" methods have been proposed which acquire one or more high-resolution reference images and a sequence of reduced dynamic data sets. This paper is devoted to the discussion of a generalized series-based dynamic imaging method, which is an optimal implementation of the data-sharing principle. Several application examples are also presented to illustrate its effectiveness for high-resolution dynamic imaging.","PeriodicalId":375408,"journal":{"name":"Proceedings International Workshop on Medical Imaging and Augmented Reality","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings International Workshop on Medical Imaging and Augmented Reality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIAR.2001.930277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Many imaging applications require the acquisition of a time series of images. In conventional Fourier transform-based imaging methods, each of these images is acquired independently. As a result, the temporal resolution possible is limited by the number of data points collected for each data set, or one often was to sacrifice spatial resolution for temporal resolution. To overcome this problem, several "data-sharing" methods have been proposed which acquire one or more high-resolution reference images and a sequence of reduced dynamic data sets. This paper is devoted to the discussion of a generalized series-based dynamic imaging method, which is an optimal implementation of the data-sharing principle. Several application examples are also presented to illustrate its effectiveness for high-resolution dynamic imaging.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
广义序列动态成像
许多成像应用需要采集时间序列的图像。在传统的基于傅里叶变换的成像方法中,每个图像都是独立获取的。因此,可能的时间分辨率受到每个数据集收集的数据点数量的限制,或者通常是为了时间分辨率而牺牲空间分辨率。为了克服这个问题,提出了几种“数据共享”方法,这些方法获取一个或多个高分辨率参考图像和一系列简化的动态数据集。本文讨论了一种基于广义序列的动态成像方法,该方法是数据共享原则的最佳实现。应用实例说明了该方法在高分辨率动态成像中的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Template-matching approach to edge detection of volume data Level set methods and image segmentation Hybrid FEM for deformation of soft tissues in surgery simulation Segmentation and analysis of leg ulcers color images Development of a method to construct three-dimensional finite element models of thoracic aortic aneurysms from MRI images
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1