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Related Concept Videos

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...

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Related Experiment Video

Updated: Jun 16, 2026

Blood Flow Imaging with Ultrafast Doppler
05:57

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

Reducing data acquisition times in phase-encoded velocity imaging using compressed sensing.

D J Holland1, D M Malioutov, A Blake

  • 1Department of Chemical Engineering and Biotechnology, University of Cambridge, New Museums Site, Pembroke Street, Cambridge CB23RA, United Kingdom. djh79@cam.ac.uk

Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|February 9, 2010
PubMed
Summary
This summary is machine-generated.

Compressed sensing (CS) accelerates phase-encoded velocity imaging by reconstructing data from fewer samples. This method achieves accurate velocity measurements in one-third the time, enabling higher resolution imaging.

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Related Experiment Videos

Last Updated: Jun 16, 2026

Blood Flow Imaging with Ultrafast Doppler
05:57

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Area of Science:

  • Magnetic Resonance Imaging
  • Fluid Dynamics
  • Image Reconstruction

Background:

  • Phase-encoded velocity imaging is crucial for quantifying fluid flow.
  • Conventional imaging techniques require extensive acquisition times, limiting resolution and speed.
  • Compressed sensing (CS) offers a potential solution for accelerating MRI data acquisition.

Purpose of the Study:

  • To develop and validate a compressed sensing (CS) method for accelerating phase-encoded velocity image acquisition.
  • To assess the accuracy and efficiency of CS for reconstructing velocity fields in fluid flow systems.
  • To demonstrate the feasibility of achieving high-resolution velocity imaging with reduced scan times.

Main Methods:

  • Utilized compressed sensing (CS) principles to reconstruct under-sampled k-space data.
  • Employed a spatial finite-differences transform for image reconstruction.
  • Incorporated prior knowledge of liquid distribution to enhance reconstruction accuracy.
  • Validated the method with simulated and experimental measurements of liquid flow in a packed bed.

Main Results:

  • Achieved accurate velocity recovery with an 11% relative error at approximately 30% k-space sampling.
  • Demonstrated total flow measurement errors below 3% for sampling fractions >= 30%.
  • Successfully reconstructed high-resolution (230 microm x 230 microm) gas-phase velocity images, which are time-prohibitive with conventional methods.

Conclusions:

  • Compressed sensing (CS) significantly accelerates phase-encoded velocity imaging acquisition.
  • CS enables quantitative velocity measurements with high accuracy and reduced scan times.
  • The accelerated acquisition allows for improved spatial resolution, mitigating partial volume effects and enhancing measurement accuracy.