Corpus ID: 7153957

Performance Evaluation of Noise Reduction Algorithm in Magnetic Resonance Images

@inproceedings{Sarode2011PerformanceEO,
  title={Performance Evaluation of Noise Reduction Algorithm in Magnetic Resonance Images},
  author={Milindkumar V. Sarode and Prashant Deshmukh},
  year={2011}
}
The objective of this paper is to do the estimation of the noise in the Magnetic Resonance images and evaluate the noise reduction algorithm present in this paper. We propose a method for reduction of Rician noise in MRI. This method shows an optimal estimation result that is more accurate in recovering the true signal from Rician noise. The method proposed specifically for Rician noise reduction, but because Rician noise can be approximated to Gaussian when SNR is high, therefore, we expect… 

Figures and Tables from this paper

Performance Evaluation of Gabor Filter in Removing Rician Noise in MR Images
TLDR
This study exhibits that the Gabor bias removal technique improved the contrast of the MR image that is found from the moderate increase in PSNR value and visual inspection by trained radiologist.
Noise Removal in Magnetic Resonance Images using Hybrid KSL Filtering Technique
TLDR
This work has introduced a novel hybrid filter to reduce random noise in MR images by the combination of Kernel, Sobel and Low-pass (KSL) filtering techniques.
Denoising Magnetic Resonance Imaging Using Fuzzy Similarity Based Filter
TLDR
The bias correction has been proposed for the removal of bias from MRI images which increases contrast and PSNR and has been tested on simulated data sets and compared with existing method.
Magnetic Resonance Image Denoising using Laplacian Filtering Technique
Magnetic Resonance image denoising is the processing of medical images to improve their appearance to human viewers, in terms of better contrast and visibility of features of interest, or to enhance
Effect of using Genetic Algorithm to denoise MRI images corrupted with Rician Noise
TLDR
The proposed technique effectively reduces the standard deviation and significantly lowers the rectified noise of Genetic Algorithm for removal of Rician Noise.
Performance Analysis for MRI denoising using Intensity Averaging Gaussian Blur Concept and Its Comparison with Wavelet Transform Method
TLDR
This method is effectively removing the noise while preserving the edge and fine information in the images by using image diffusion and anisotropic method to estimate phase error at each pixel and convolution and Gaussian blurring method for amplitude correction.
Noise Estimation, Noise Reduction and Intensity Inhomogeneity Correction in MRI Images of the Brain
Rician noise and intensity inhomogeneity are two common types of image degradation that manifest in the acquisition of magnetic resonance imaging (MRI) system images of the brain. Many noise
Brain Tumor Analysis of Rician Noise Affected MRI Images
TLDR
This paper investigates the performance evaluation of different image matting techniques to extract tumor from Rician noise affected MRI brain images.
Application of Genetic Algorithm in Denoising MRI Images Clouded with Rician Noise
TLDR
New genetic manipulator is used that blends crossover and adaptive mutation to improve the convergence rate and solution quality of GA and efficaciously reduces the standard deviation and significantly lowers the rectified noise after the filtering was performed.
Enhancement of Computed Tomography Image using Laplacian Filtering Technique
Computed tomography image enhancement is the processing of medical images to improve their appearance to human viewers, in terms of better contrast and visibility of features of interest, or to
...
1
2
...

References

SHOWING 1-10 OF 17 REFERENCES
Noise Reduction in Magnetic Resonance Images using Wave Atom Shrinkage
De-noising is always a challenging problem in magnetic resonance imaging and important for clinical diagnosis and computerized analysis, such as tissue classification and segmentation. It is well
A Nonlocal Maximum Likelihood Estimation Method for Rician Noise Reduction in MR Images
TLDR
It is demonstrated that NLML performs better than the conventional local maximum likelihood (LML) estimation method in preserving and defining sharp tissue boundaries in terms of a well-defined sharpness metric while also having superior performance in method error.
Wavelet-based Rician noise removal for magnetic resonance imaging
  • R. Nowak
  • Mathematics, Medicine
    IEEE Trans. Image Process.
  • 1999
TLDR
A novel wavelet-domain filter that adapts to variations in both the signal and the noise is presented, which is especially problematic in low signal-to-noise ratio (SNR) regimes.
MRI denoising via phase error estimation
TLDR
A new scheme based on iteratively applying a series of non-linear filters is proposed, each used to modify the estimate into greater agreement with one piece of knowledge about the problem, until the output converges to a stable estimate.
Noise and filtration in magnetic resonance imaging.
TLDR
Noise in two-dimensional Fourier transform magnetic resonance images has been investigated using noise power spectra and measurements of standard deviation, finding the noise of unfiltered images is found to be white, and the choice of the temporal filter and sampling interval affects the noise in a manner predicted by sampling theory.
Measurement of signal intensities in the presence of noise in MR images.
TLDR
This report describes how to extract true intensity measurements in the presence of noise in magnetic resonance imaging.
A universal noise removal algorithm with an impulse detector
TLDR
The result is a new filter capable of reducing both Gaussian and impulse noises from noisy images effectively, which performs remarkably well, both in terms of quantitative measures of signal restoration and qualitative judgements of image quality.
Statistical Based Impulsive Noise Removal in Digital Radiography
TLDR
A new filter to restore radiographic images corrupted by impulsive noise is proposed, based on a switching scheme where all the pulses are first detected and then corrected through a median filter, which is able to reliably estimate the sensor gain.
$1/f$ Noise in Diffuse Optical Imaging and Wavelet-Based Response Estimation
TLDR
This work extends a previously proposed method for fMRI to estimate the parameters of a linear model of DOI time series and benefits from the whitening property of the discrete wavelet transform (DWT), which approximately decorrelates long-memory noise processes.
Noise reduction using an undecimated discrete wavelet transform
TLDR
A new nonlinear noise reduction method is presented that uses the discrete wavelet transform instead of the usual orthogonal one, resulting in a significantly improved noise reduction compared to the original wavelet based approach.
...
1
2
...