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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...
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
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,...
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...

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Related Experiment Video

Updated: Jul 7, 2026

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition
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Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition

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Wavelet-based Rician noise removal for magnetic resonance imaging.

R D Nowak1

  • 1Dept. of Electr. and Comput. Eng., Rice Univ., Houston, TX 77251-1892, USA. nowak@egr.msu.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 13, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a new wavelet-domain filter to remove Rician noise from magnetic resonance images. The filter effectively separates signal from noise, improving image quality, especially in low signal-to-noise ratio (SNR) conditions.

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Published on: January 25, 2012

Area of Science:

  • Medical Imaging
  • Signal Processing
  • Applied Mathematics

Background:

  • Magnetic resonance (MR) magnitude image data follow a Rician distribution.
  • Rician noise is signal-dependent, unlike Gaussian noise, making signal-noise separation challenging.
  • In low signal-to-noise ratio (SNR) scenarios, Rician noise causes fluctuations and signal-dependent bias, reducing image contrast.

Purpose of the Study:

  • To investigate wavelet-domain filtering techniques for Rician noise removal in MR images.
  • To develop a novel filter capable of adapting to signal and noise variations.

Main Methods:

  • Wavelet-domain filtering was employed for noise reduction.
  • A new adaptive wavelet-domain filter was designed and implemented.

Main Results:

  • The proposed filter effectively removes Rician noise from MR images.
  • The filter demonstrates adaptability to varying signal and noise levels.
  • Improved image contrast and reduced bias were observed, particularly in low SNR regions.

Conclusions:

  • Wavelet-domain filtering offers a viable approach for Rician noise removal.
  • The novel adaptive filter enhances MR image quality by addressing signal-dependent noise and bias.
  • This method is particularly beneficial for low SNR imaging applications.