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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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The number of nuclear spins aligned in the lower energy state is slightly greater than those in the higher energy state. In the presence of an external magnetic field, as the spins precess at the Larmor frequency, the excess population results in a net magnetization oriented along the z axis. When a pulse or a short burst of radio waves at the Larmor frequency is applied along the x axis, the coupling of frequencies causes resonance and flips the nuclear spins of the excess population from the...
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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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Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
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Performance analysis for magnetic resonance imaging with nonlinear encoding fields.

Kelvin J Layton1, Mark Morelande, Peter M Farrell

  • 1Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia. klayton@unimelb.edu.au

IEEE Transactions on Medical Imaging
|October 4, 2011
PubMed
Summary
This summary is machine-generated.

Nonlinear spatial encoding fields in magnetic resonance imaging (MRI) offer faster scans but complicate analysis. This study introduces a new, efficient metric to evaluate signal-to-noise ratio (SNR) performance for these advanced MRI techniques.

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Signal Processing

Background:

  • Traditional linear gradients in magnetic resonance imaging (MRI) have limitations in speed and flexibility.
  • Nonlinear spatial encoding fields in MRI promise reduced imaging times but present analysis challenges.
  • Assessing performance metrics like resolution and signal-to-noise ratio (SNR) is complex with nonlinear fields.

Purpose of the Study:

  • To develop a general formulation for analyzing imaging schemes with arbitrary encoding fields.
  • To derive a practical and computationally efficient performance metric for nonlinear MRI.
  • To focus on the signal-to-noise ratio (SNR) characteristics influenced by nonlinear encoding.

Main Methods:

  • Formulation of a general framework for performance analysis of arbitrary encoding fields.
  • Derivation of a novel, computationally efficient metric for assessing SNR performance.
  • Examination of pixel variance as a key indicator, addressing computational feasibility.

Main Results:

  • A practical and efficient performance metric for nonlinear MRI was derived.
  • The new metric allows for feasible analysis of SNR in complex encoding schemes.
  • Simulation examples demonstrated the metric's utility and efficiency.

Conclusions:

  • The developed metric provides a valuable tool for evaluating nonlinear MRI performance.
  • This work facilitates the adoption of advanced nonlinear encoding techniques for faster MRI.
  • The metric addresses the challenge of analyzing spatially varying SNR in nonlinear MRI.