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Electromagnetic Noise Characterization and Suppression in Low-Field MRI Systems.

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This study presents a practical protocol to identify and reduce electromagnetic noise in low-field MRI systems. The developed method allows these systems to operate near their theoretical thermal noise limits, improving image quality.

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Electrical Engineering

Background:

  • Low-field MRI systems are susceptible to electromagnetic interference (EMI).
  • Operating near the thermal noise limit is crucial for optimal signal-to-noise ratio (SNR).
  • Existing protocols for noise suppression in low-field MRI are often impractical.

Purpose of the Study:

  • To develop and validate a practical protocol for identifying and suppressing electromagnetic noise in low-field MRI systems.
  • To enable low-field MRI operation close to the theoretical thermal noise limit.
  • To provide guidance for integrating additional system components without compromising SNR.

Main Methods:

  • A systematic, stepwise methodology was developed.
  • Diagnostic measurements, hardware isolation, and best practices for cabling and shielding were employed.
  • Noise measurements were conducted during incremental system assembly, with and without a human subject.

Main Results:

  • Key sources of EMI were identified and their impact quantified.
  • Final system configurations achieved noise levels within 1.5x the theoretical thermal bound with a subject present.
  • Image reconstructions demonstrated a direct correlation between system noise and image quality.

Conclusions:

  • The proposed protocol enables low-field MRI systems to operate near fundamental noise limits under realistic conditions.
  • The framework offers guidance for integrating new components like gradient drivers and automatic tuning networks.
  • Successful noise suppression leads to improved image quality and system performance.