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Related Concept Videos

Downsampling01:20

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
Upsampling01:22

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next sampling...
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...

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Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
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Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

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3D undersampled golden-radial phase encoding for DCE-MRA using inherently regularized iterative SENSE.

Claudia Prieto1, Sergio Uribe, Reza Razavi

  • 1King's College London, Division of Imaging Sciences, NIHR Biomedical Research Centre at Guy's & St Thomas' Foundation Trust London, United Kingdom. claudia.prieto@kcl.ac.uk

Magnetic Resonance in Medicine
|July 29, 2010
PubMed
Summary

This study introduces a novel dynamic contrast-enhanced MR angiography method for improved imaging. It allows retrospective adjustment of spatial and temporal resolution, enhancing visualization of small vessels and temporal phases.

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Area of Science:

  • Magnetic Resonance Imaging
  • Medical Imaging
  • Radiology

Background:

  • Dynamic contrast-enhanced MR angiography (DCE-MRA) is limited by the need for high spatial and temporal resolution.
  • Existing undersampling techniques often fix the spatial-temporal resolution tradeoff, which is suboptimal for dynamic processes.
  • Predicting contrast bolus dynamics and varying image quality needs during DCE-MRA is challenging.

Purpose of the Study:

  • To develop a novel undersampled approach for DCE-MRA enabling retrospective adaptation of spatial and temporal resolution.
  • To overcome the limitations of fixed resolution tradeoffs in current DCE-MRA techniques.
  • To improve image quality and flexibility in DCE-MRA for better visualization of vascular dynamics.

Main Methods:

  • A highly undersampled approach combining a 3D radial phase encoding trajectory with golden angle ordering.
  • Non-Cartesian Sensitivity Encoding (SENSE) reconstruction utilizing regularization images for stabilization.
  • Retrospective reconstruction allowing adjustment of temporal resolutions from 1.2 to 8.1 seconds.

Main Results:

  • Demonstrated feasibility on a numerical phantom and in 3D intracranial DCE-MRA of healthy volunteers.
  • Achieved retrospective adaptation of spatial and temporal resolution from acquired data.
  • Provided good depiction of small vessels and clear distinction of different temporal phases during contrast bolus passage.

Conclusions:

  • The proposed method offers a flexible and effective solution for DCE-MRA, overcoming limitations of fixed resolution tradeoffs.
  • Retrospective adjustment of resolution enhances the ability to visualize dynamic vascular changes and fine details.
  • This technique holds promise for improving diagnostic capabilities in DCE-MRA applications.