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Reseach Article

Noise Removal in Magnetic Resonance Images using Hybrid KSL Filtering Technique

by C. Lakshmi Devasena, M. Hemalatha
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 8
Year of Publication: 2011
Authors: C. Lakshmi Devasena, M. Hemalatha
10.5120/3324-4571

C. Lakshmi Devasena, M. Hemalatha . Noise Removal in Magnetic Resonance Images using Hybrid KSL Filtering Technique. International Journal of Computer Applications. 27, 8 ( August 2011), 1-4. DOI=10.5120/3324-4571

@article{ 10.5120/3324-4571,
author = { C. Lakshmi Devasena, M. Hemalatha },
title = { Noise Removal in Magnetic Resonance Images using Hybrid KSL Filtering Technique },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 8 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number8/3324-4571/ },
doi = { 10.5120/3324-4571 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:12.965691+05:30
%A C. Lakshmi Devasena
%A M. Hemalatha
%T Noise Removal in Magnetic Resonance Images using Hybrid KSL Filtering Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 8
%P 1-4
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In Medical Diagnostic, Magnetic Resonance Images play a major role. Magnetic Resonance images are normally corrupted by random noise from the measurement process complicating the automatic feature extraction and analysis of clinical data. Because of this reason noise removal methods have been customarily applied to improve MR image quality. This work proposed a new scheme based on applying a series of filters, each used to modify the estimate into greater agreement, so that the output converges to a stable estimate providing noise free image. In this work, we have introduced a novel hybrid filter to reduce random noise in MR images by the combination of Kernel, Sobel and Low-pass (KSL) filtering techniques. The proposed method has been implemented using Matlab and compared with related state of art methods over synthetic and real clinical MR images showing a superior performance in all cases analyzed.

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Index Terms

Computer Science
Information Sciences

Keywords

Kernel Operator Low-pass Filter Noise Removal Sobel Operator