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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Related Experiment Video

Updated: Jun 28, 2026

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
06:56

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Published on: January 7, 2021

Estimating Motion From MRI Data.

Cengizhan Ozturk1, J Andrew Derbyshire, Elliot R McVeigh

  • 1MEMBER, IEEE, The Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey, and also with the National Institutes of Health, National Heart, Lung, and Blood Institute (NHLBI), Bethesda, MD 20892-1538 USA (e-mail: ozturkc@nhlbi.nih.gov ).

Proceedings of the IEEE. Institute of Electrical and Electronics Engineers
|October 30, 2008
PubMed
Summary
This summary is machine-generated.

Magnetic resonance imaging (MRI) offers advanced capabilities for tracking tissue and blood flow motion. New methods utilize MRI phase information to precisely encode displacement and velocity for cardiovascular imaging.

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Image Processing

Background:

  • Magnetic resonance imaging (MRI) excels in soft tissue contrast and flexible image acquisition.
  • Tissue boundaries and edges can be tracked from temporal sequences of MR images.
  • MRI signal manipulation allows for the introduction of patterns for motion tracking.

Purpose of the Study:

  • To review methods for encoding, imaging, and modeling motion fields using MRI.
  • To highlight MRI's potential in cardiovascular and soft tissue imaging.
  • To explain how MRI phase information can directly encode motion parameters.

Main Methods:

  • Utilizing MR saturation techniques to create temporary magnetic tags for motion tracking.
  • Preserving pixel phase information during image reconstruction.
  • Applying image processing techniques to track tissue boundaries from image sequences.

Main Results:

  • Demonstration of MRI's capability to measure blood flow and tissue motion.
  • Introduction of phase-based encoding for displacement, velocity, and acceleration.
  • Successful application of motion modeling in cardiovascular and soft tissue imaging.

Conclusions:

  • MRI is an ideal modality for quantitative motion analysis in biological tissues.
  • Phase-based MRI techniques offer precise encoding of motion dynamics.
  • Advanced MRI methods are crucial for understanding cardiovascular and soft tissue mechanics.