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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...
Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...

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Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
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Suppression of slice selection axis motion artifacts in MRI.

M Hedley1, H Yan

  • 1Dept. of Electr. Eng., Sydney Univ., NSW.

IEEE Transactions on Medical Imaging
|January 1, 1992
PubMed
Summary

Patient motion in magnetic resonance imaging (MRI) creates image artifacts. This study presents a new algorithm to reduce motion artifacts, effective for both periodic and non-periodic movements, even with noise.

Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Image Reconstruction

Background:

  • Patient motion during Magnetic Resonance Imaging (MRI) acquisition introduces artifacts like blurring and ghosting in 2D Fourier Transform (2DFT) images.
  • Existing techniques, such as the one proposed by T. Mitsa et al. (1990), primarily address artifacts caused by periodic motion along the slice selection axis.

Purpose of the Study:

  • To develop and present a novel algorithm for suppressing motion artifacts in MRI.
  • To overcome the limitations of previous methods by addressing non-periodic motion.
  • To evaluate the algorithm's performance under various conditions, including noise and in-plane motion.

Main Methods:

  • A new motion artifact suppression algorithm was developed for MRI.
  • The algorithm was validated using simulated phantom data with controlled motion.

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  • Performance was assessed in the presence of simulated noise and motion within the imaging plane.

    • Main Results:

    • The proposed algorithm effectively suppresses motion artifacts in MRI.
    • The technique is not limited to periodic motion and demonstrates robustness.
    • Successful performance was observed even when noise and in-plane motion were present.

    Conclusions:

    • A versatile algorithm for reducing MRI motion artifacts has been developed.
    • This method offers an improvement over techniques restricted to periodic motion.
    • The algorithm shows promise for enhancing image quality in challenging acquisition scenarios.