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Related Concept Videos

Spherical Coordinates01:23

Spherical Coordinates

Spherical coordinate systems are preferred over Cartesian, polar, or cylindrical coordinates for systems with spherical symmetry. For example, to describe the surface of a sphere, Cartesian coordinates require all three coordinates. On the other hand, the spherical coordinate system requires only one parameter: the sphere's radius. As a result, the complicated mathematical calculations become simple. Spherical coordinates are used in science and engineering applications like electric and...
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position with respect to time...

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Prospective motion correction for and susceptibility mapping using spherical navigators.

Miriam Hewlett1,2, Omer Oran3, Junmin Liu1

  • 1Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada.

Magnetic Resonance in Medicine
|December 4, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new navigator-based method for prospective motion correction (PMC) and field shift correction, significantly improving MRI quantitative mapping accuracy in the brain.

Keywords:
brainnavigatorsprospective motion correctionsusceptibility mapping

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Physics
  • Neuroimaging

Background:

  • Motion artifacts are a major challenge in quantitative MRI, degrading image quality and map accuracy.
  • Accurate and susceptibility mapping are crucial for various neurological applications.

Purpose of the Study:

  • To develop and evaluate a purely navigator-based approach for prospective motion correction (PMC).
  • To simultaneously correct for motion and zeroth-order field shifts during MRI acquisition.

Main Methods:

  • Spherical navigators (SNAVs) combined with FID readouts (FIDSNAVs) were used for simultaneous motion and field shift measurement.
  • FIDSNAVs were interleaved with a multi-echo gradient echo sequence for PMC, alongside retrospective correction.
  • Experiments were conducted on a 3T scanner with a 32-channel head coil and tested in volunteers with real motion data.

Main Results:

  • PMC effectively reduced artifacts, especially at shorter echo times.
  • Retrospective correction was vital for artifact reduction at longer echo times.
  • Both PMC and retrospective correction improved the accuracy of and susceptibility maps, with residual artifacts in severe motion cases.

Conclusions:

  • The FIDSNAV approach enables simultaneous motion and field correction without extra hardware.
  • This method enhances the fidelity of quantitative MRI mapping in the presence of subject motion.
  • The technique holds promise for improving diagnostic accuracy in neuroimaging.