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Mammographic Microcalcifications Detection using Discrete Wavelet Transform

by Nizar Ben Hamad, Khaled Taouil, Med Salim Bouhlel
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 21
Year of Publication: 2013
Authors: Nizar Ben Hamad, Khaled Taouil, Med Salim Bouhlel
10.5120/10758-5695

Nizar Ben Hamad, Khaled Taouil, Med Salim Bouhlel . Mammographic Microcalcifications Detection using Discrete Wavelet Transform. International Journal of Computer Applications. 64, 21 ( February 2013), 17-22. DOI=10.5120/10758-5695

@article{ 10.5120/10758-5695,
author = { Nizar Ben Hamad, Khaled Taouil, Med Salim Bouhlel },
title = { Mammographic Microcalcifications Detection using Discrete Wavelet Transform },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 21 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number21/10758-5695/ },
doi = { 10.5120/10758-5695 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:17:13.639936+05:30
%A Nizar Ben Hamad
%A Khaled Taouil
%A Med Salim Bouhlel
%T Mammographic Microcalcifications Detection using Discrete Wavelet Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 21
%P 17-22
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Breast cancer can be diagnosed with an early training course by detecting the presence of microcalcifications in screening mammograms. The multiresolution analysis using discrete wavelet transform presents characteristics which can be exploited to develop tools for detection of microcalcifications. The objective of this work is to study the best type of wavelet and the optimal level of decomposition for a better detection. The approach is divided into two phases. The first phase of the algorithm consists on multiresolution analysis based on 1-D discrete wavelet transform over profiles of microcalcifications extracted from mammographic images. This analysis is carried out with several families of wavelets. The second phase of the algorithm is interested in the validation of the results of the first. In this stage, we apply 2-D discrete wavelet transform in analysis and synthesis on screening mammograms extracted from the mini-MIAS database (Mammographic Image Analysis Society) in order to detect the microcalcifications.

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Index Terms

Computer Science
Information Sciences

Keywords

Breast cancer Digital Mammograms Microcalcification Discrete Wavelet Transform Multiresolution analysis

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