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Multiplicative Noise Reduction using Fuzzy Logic and Feature Analysis of Ultrasound Images

Published on September 2015 by Jaffar Baig M.A, Bindu A Thomas, Stafford Michahial
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National Conference “Electronics, Signals, Communication and Optimization"
Foundation of Computer Science USA
NCESCO2015 - Number 2
September 2015
Authors: Jaffar Baig M.A, Bindu A Thomas, Stafford Michahial
6aad6908-75b4-45a5-b9ee-715c568f23bc

Jaffar Baig M.A, Bindu A Thomas, Stafford Michahial . Multiplicative Noise Reduction using Fuzzy Logic and Feature Analysis of Ultrasound Images. National Conference “Electronics, Signals, Communication and Optimization". NCESCO2015, 2 (September 2015), 29-34.

@article{
author = { Jaffar Baig M.A, Bindu A Thomas, Stafford Michahial },
title = { Multiplicative Noise Reduction using Fuzzy Logic and Feature Analysis of Ultrasound Images },
journal = { National Conference “Electronics, Signals, Communication and Optimization" },
issue_date = { September 2015 },
volume = { NCESCO2015 },
number = { 2 },
month = { September },
year = { 2015 },
issn = 0975-8887,
pages = { 29-34 },
numpages = 6,
url = { /proceedings/ncesco2015/number2/22305-5319/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference “Electronics, Signals, Communication and Optimization"
%A Jaffar Baig M.A
%A Bindu A Thomas
%A Stafford Michahial
%T Multiplicative Noise Reduction using Fuzzy Logic and Feature Analysis of Ultrasound Images
%J National Conference “Electronics, Signals, Communication and Optimization"
%@ 0975-8887
%V NCESCO2015
%N 2
%P 29-34
%D 2015
%I International Journal of Computer Applications
Abstract

Ultrasound imaging is a vital tool for diagnosis in the field of biomedical imaging used to detect various types of abnormalities or diseases. Unfortunately, the multiplicative noise which coexists in these images makes it very challenging and difficult for doctors to provide accurate diagnosis. Multiplicative noise reduction is thus an important task for developing effective diagnosis system. In this paper, fuzzy logic is implemented to reduce multiplicative noise. Feature analysis like segmentation, determining region of interest and seed point selection is carried out and different existing de-noising algorithms are compared with the proposed method. The paper presents performance comparisons in terms of improvement in signal to noise ratio (SNR) of the proposed scheme with respect to MSE (Mean Square Error).

References
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Index Terms

Computer Science
Information Sciences

Keywords

Multiplicative Noise Speckle Noise Fuzzy Logic Ultrasound Denoising Despeckle Mean Square Error Peak Signal To Noise Ratio.