2017
DOI: 10.1002/ima.22230
|View full text |Cite
|
Sign up to set email alerts
|

Rician noise removal in magnitude MRI images using efficient anisotropic diffusion filtering

Abstract: In this article, a new methodology for denoising of Rician noise in Magnetic Resonance Images (MRI) is presented. MRI imaging creates a distinctive view into the interior of a human body and has become an essential tool of clinical diagnosis. However, Rician noise is a type of artifact inherent to the acquisition process of the magnitude MRI image, making diagnosis difficult. We proposed a moment‐based Rician noise reduction technique in anisotropic diffusion filtering. We extend the work of the classical anis… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
15
0

Year Published

2018
2018
2022
2022

Publication Types

Select...
6
3

Relationship

0
9

Authors

Journals

citations
Cited by 35 publications
(17 citation statements)
references
References 31 publications
0
15
0
Order By: Relevance
“…In MR images low signal intensities (Signal to Noise Ratio (SNR) < 2) are consequently biased to noise which leads to blurring of significant details of images like edges and boundaries of tissue parts or structural details of an organ. A simple scheme is initiated to correct the bias due to the Rician distribution of the noisy magnitude data (15) . The additional noise in MR image is smoothed with the weights that are computed using pre-smoothed MR images.…”
Section: Methodsmentioning
confidence: 99%
“…In MR images low signal intensities (Signal to Noise Ratio (SNR) < 2) are consequently biased to noise which leads to blurring of significant details of images like edges and boundaries of tissue parts or structural details of an organ. A simple scheme is initiated to correct the bias due to the Rician distribution of the noisy magnitude data (15) . The additional noise in MR image is smoothed with the weights that are computed using pre-smoothed MR images.…”
Section: Methodsmentioning
confidence: 99%
“…Rician noise produced from the original frequency domain measurements (complex Gaussian noise) to corrupt the MR Image [26]. The Rician probability density function ( ) for the noised image is calculated according to equation 1.…”
Section: Proposed Methodsmentioning
confidence: 99%
“…The images provided by the Harvard's Whole Brain Atlas are raw images and are affected by Rician noise. The selected ROIs are denoised by using an anisotropic diffusion filter [23,24]. The anisotropic diffusion filtering provides reliable noise removing while very satisfactory edge-preserving results are achieved.…”
Section: Mathematical Approachesmentioning
confidence: 99%
“…The analysis was performed in two datasets; D1 contains raw images from the Harvard's Whole Brain Atlas that are affected by noises with Rician distribution. D2 contains denoised images by using an anisotropic diffusion filter [23,24]. The results are compared in terms of the noise effect on the proposed method.…”
Section: Introductionmentioning
confidence: 99%