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Related Experiment Videos

Time-resolved MR imaging by automatic data segmentation

J O Fredrickson1, N J Pelc

  • 1Department of Radiology, Richard M. Lucas Center for Magnetic Resonance Spectroscopy and Imaging, Stanford University, CA 94305-5488.

Journal of Magnetic Resonance Imaging : JMRI
|March 1, 1994
PubMed
Summary
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This study introduces a novel time-resolved imaging method using view order selection. It enables flexible adjustments between imaging speed and temporal resolution for applications like cardiac and respiratory motion.

Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Physics

Background:

  • Time-resolved imaging is crucial for dynamic physiological processes.
  • Conventional methods often face limitations in balancing imaging speed and temporal resolution.
  • Cardiac and respiratory motion introduce challenges in acquiring high-resolution dynamic data.

Purpose of the Study:

  • To present a flexible time-resolved imaging method.
  • To enable a trade-off between imaging time and temporal resolution.
  • To apply this technique to cardiac and respiratory motion compensation.

Main Methods:

  • A view order selection technique for raw data segmentation.
  • Automatic segmentation into temporal frames.
  • Implementation within various pulse sequences, including phase-contrast imaging.

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Main Results:

  • Achieved rapid data acquisition comparable to conventional gated sequences.
  • Enabled imaging within a breath-hold interval by reducing temporal resolution.
  • Allowed accurate time-averaged flow quantitation.
  • Demonstrated capability to resolve cardiac and respiratory motion cycles.

Conclusions:

  • The presented method offers a flexible approach to time-resolved imaging.
  • It allows for efficient data acquisition and motion compensation.
  • This technique has broad applicability in dynamic physiological imaging and flow quantitation.