Improving the Resolution of MPM Recovered Relaxometry Parameters with Proper Time Domain Sampling

IF 1.1 4区 物理与天体物理 Q4 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL
M. Parziale, D. Woertge, B. Mohebbi, J. Claussen, M. P. Augustine
{"title":"Improving the Resolution of MPM Recovered Relaxometry Parameters with Proper Time Domain Sampling","authors":"M. Parziale,&nbsp;D. Woertge,&nbsp;B. Mohebbi,&nbsp;J. Claussen,&nbsp;M. P. Augustine","doi":"10.1007/s00723-023-01596-x","DOIUrl":null,"url":null,"abstract":"<div><p>The matrix pencil method (MPM) is a powerful tool for processing transient nuclear magnetic resonance (NMR) relaxation signals with promising applications to increasingly complex problems. In the absence of signal noise, the eigenvalues recovered from an MPM treatment of transient relaxometry data reduce to relaxation coefficients that can be used to calculate relaxation time constants for known sampling time ∆t. The MPM eigenvalue and relaxation coefficient equality as well as the resolution of similar eigenvalues and thus relaxation coefficients degrade in the presence of signal noise. The relaxation coefficient ∆t dependence suggests one way to improve MPM resolution by choosing ∆t values such that the differences between all the relaxation coefficient values are maximized. This work develops mathematical machinery to estimate the best ∆t value for sampling damped, transient relaxation signals such that MPM data analysis recovers a maximum number of time constants and amplitudes given inherent signal noise. Analytical and numerical reduced dimension MPM is explained and used to compare computer-generated data with and without added noise as well as treat real measured signals. Finally, the understanding gleaned from this effort is used to predict the best data sampling time to use for non-discrete, distributions of relaxation variables.</p></div>","PeriodicalId":469,"journal":{"name":"Applied Magnetic Resonance","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00723-023-01596-x.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Magnetic Resonance","FirstCategoryId":"101","ListUrlMain":"https://link.springer.com/article/10.1007/s00723-023-01596-x","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, ATOMIC, MOLECULAR & CHEMICAL","Score":null,"Total":0}
引用次数: 0

Abstract

The matrix pencil method (MPM) is a powerful tool for processing transient nuclear magnetic resonance (NMR) relaxation signals with promising applications to increasingly complex problems. In the absence of signal noise, the eigenvalues recovered from an MPM treatment of transient relaxometry data reduce to relaxation coefficients that can be used to calculate relaxation time constants for known sampling time ∆t. The MPM eigenvalue and relaxation coefficient equality as well as the resolution of similar eigenvalues and thus relaxation coefficients degrade in the presence of signal noise. The relaxation coefficient ∆t dependence suggests one way to improve MPM resolution by choosing ∆t values such that the differences between all the relaxation coefficient values are maximized. This work develops mathematical machinery to estimate the best ∆t value for sampling damped, transient relaxation signals such that MPM data analysis recovers a maximum number of time constants and amplitudes given inherent signal noise. Analytical and numerical reduced dimension MPM is explained and used to compare computer-generated data with and without added noise as well as treat real measured signals. Finally, the understanding gleaned from this effort is used to predict the best data sampling time to use for non-discrete, distributions of relaxation variables.

Abstract Image

适当的时域采样提高MPM恢复弛豫参数的分辨率
矩阵铅笔法(matrix pencil method, MPM)是一种处理瞬态核磁共振(NMR)松弛信号的强大工具,在日益复杂的问题中具有广阔的应用前景。在没有信号噪声的情况下,从瞬态弛豫数据的MPM处理中恢复的特征值减少为松弛系数,可用于计算已知采样时间∆t的松弛时间常数。在存在信号噪声的情况下,MPM特征值和松弛系数相等,相似特征值和松弛系数的分辨率降低。松弛系数∆t依赖性提出了一种提高MPM分辨率的方法,即选择∆t值,使所有松弛系数值之间的差异最大化。这项工作开发了数学机制来估计采样阻尼瞬态松弛信号的最佳∆t值,使MPM数据分析恢复给定固有信号噪声的最大时间常数和幅度。解释了解析和数值降维MPM,并将其用于比较有和没有添加噪声的计算机生成数据以及处理实际测量信号。最后,从这项工作中获得的理解用于预测用于松弛变量的非离散分布的最佳数据采样时间。
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
Applied Magnetic Resonance
Applied Magnetic Resonance 物理-光谱学
CiteScore
1.90
自引率
10.00%
发文量
59
审稿时长
2.3 months
期刊介绍: Applied Magnetic Resonance provides an international forum for the application of magnetic resonance in physics, chemistry, biology, medicine, geochemistry, ecology, engineering, and related fields. The contents include articles with a strong emphasis on new applications, and on new experimental methods. Additional features include book reviews and Letters to the Editor.
×
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