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Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
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Correcting slice selectivity in hard pulse sequences.

David M Grodzki1, Peter M Jakob, Bjoern Heismann

  • 1Department of Experimental Physics 5, University of Wuerzburg, Germany. david.grodzki.ext@siemens.com

Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|November 4, 2011
PubMed
Summary
This summary is machine-generated.

This study explores using magnetic resonance imaging (MRI) pulse excitation profiles for better image quality. A new algorithm corrects for excitation profile artifacts, enhancing MRI scans when the profile

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Area of Science:

  • Medical Imaging
  • Magnetic Resonance Imaging (MRI)
  • Biomedical Engineering

Background:

  • Many magnetic resonance imaging (MRI) sequences utilize non-selective hard pulse excitation.
  • This excitation occurs concurrently with imaging gradients, potentially introducing artifacts.
  • The sinc-shaped frequency excitation profiles of these pulses are critical but can impact image fidelity.

Purpose of the Study:

  • To investigate the extent to which sinc-shaped excitation profiles can be used for MRI without generating artifacts.
  • To develop and validate a correction algorithm to mitigate the influence of excitation profiles on image quality.
  • To assess the impact of the excitation profile's first minimum position relative to the imaged object on image enhancement.

Main Methods:

  • Analysis of sinc-shaped frequency excitation profiles in MRI sequences.
  • Development of a novel correction algorithm to eliminate excitation profile influence.
  • Validation using both phantom and in vivo MRI measurements.

Main Results:

  • The study demonstrates that sinc-shaped excitation profiles can be leveraged for imaging.
  • The proposed correction algorithm effectively eliminates artifacts caused by excitation profiles.
  • Enhanced image quality was achieved in phantom and in vivo studies.

Conclusions:

  • Optimizing the position of the excitation profile's first minimum outside the imaged object is key for artifact reduction.
  • The developed correction algorithm significantly improves MRI image quality.
  • This work provides a method to enhance MRI scans by managing excitation profile characteristics.