All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Exploring the potential of PCA-based quantitation of NMR signals in T-1 relaxometry

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10439416" target="_blank" >RIV/00216208:11320/21:10439416 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=fSh~plcq_a" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=fSh~plcq_a</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.jmr.2021.106965" target="_blank" >10.1016/j.jmr.2021.106965</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring the potential of PCA-based quantitation of NMR signals in T-1 relaxometry

  • Original language description

    Principal component analysis (PCA) has proved to be a powerful technique for processing NMR data. It is particularly useful in signal quantitation where it often provides better results compared to a direct integration of individual signals. In the present work, we recapitulate the principles and theoretical framework underlying PCA-based quantitation with a special focus on T-1 relaxometry. We show that under commonly encountered conditions, this approach can provide up to similar to 4-fold improvement in scatter of points in magnetization build-up curves compared to direct integration. Best practices to optimize the PCA performance in measuring the total magnetization are discussed, including minimization of the number of signal-related principal components and a proper selection of FT parameters and data quantitation intervals. For signals consisting of distinct relaxation components, formulas are provided for resolving the components relaxation and illustrated on a real-data example. In addition to the problem of quantitation, the use of PCA in denoising of partially relaxed spectra is discussed in connection with such applications as line shape analysis and monitoring relaxation of individual spectral components. (C) 2021 Elsevier Inc. All rights reserved.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10301 - Atomic, molecular and chemical physics (physics of atoms and molecules including collision, interaction with radiation, magnetic resonances, Mössbauer effect)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Magnetic Resonance

  • ISSN

    1090-7807

  • e-ISSN

  • Volume of the periodical

    326

  • Issue of the periodical within the volume

    18 March 2021

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    10

  • Pages from-to

    106965

  • UT code for WoS article

    000644070400005

  • EID of the result in the Scopus database

    2-s2.0-85103114000