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2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

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Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
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An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a low-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.
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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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A mass spectrum is the graphical representation of the relative abundance of the charged fragments in an analyte plotted against their mass-to-charge ratio (m/z). The plot's x axis represents the ratio of the mass of the charged fragment to the elementary charge it carries. The y axis of the plot represents the relative abundance of each charged species. The relative abundance is calculated from the signal intensity of each charged species recorded at the detector. The most intense signal...
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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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This lesson details the instrumentation of a mass spectrometer—a physical instrument to perform mass spectrometry on analyte molecules and record the characteristic mass spectra. This is achieved via three chief functions:
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Incomplete spectrum QSM using support information.

Patrick Fuchs1, Karin Shmueli1

  • 1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.

Frontiers in Neuroscience
|May 4, 2023
PubMed
Summary

This study introduces an incomplete spectrum approach for quantitative magnetic susceptibility mapping (QSM), improving reconstructions by addressing ill-posed frequency-space data. The method shows promise, especially with added regularization, offering an alternative to existing QSM techniques.

Keywords:
Fourier transformQSMcompressed sensingdipole inversionincomplete spectrummagnetic susceptibilityregularization

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Area of Science:

  • Medical Imaging
  • Computational Physics
  • Applied Mathematics

Background:

  • Quantitative Magnetic Susceptibility Mapping (QSM) is crucial for neuroimaging.
  • The field-to-source problem in QSM is ill-posed due to zero/small values in the dipole kernel, causing artifacts.
  • Existing methods like compressed sensing have limitations.

Purpose of the Study:

  • To apply the incomplete spectrum approach to address the ill-posed nature of QSM.
  • To evaluate the performance of incomplete spectrum QSM against state-of-the-art methods.
  • To investigate the impact of regularization on reconstruction quality.

Main Methods:

  • The incomplete spectrum method was tuned for QSM using a simulated dataset.
  • Reconstructions were validated on human brain MRI data.
  • Comparisons were made with FANSI, nonlinear dipole inversion, and thresholded k-space division.

Main Results:

  • Without regularization, incomplete spectrum QSM slightly outperformed thresholded k-space division.
  • It yielded comparable susceptibility values in iron-rich regions to advanced methods.
  • With L1-wavelet regularization, results mirrored compressed sensing reconstructions.

Conclusions:

  • The incomplete spectrum approach offers a novel way to handle ill-posed frequency-space data in QSM.
  • This method provides a viable alternative, particularly when combined with regularization techniques.
  • It has the potential to improve the quality and reliability of QSM reconstructions.