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Breast Cancer Diagnosis by CAD

by Nidhal K. El Abbadi, Elaf J. Al Taee
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 5
Year of Publication: 2014
Authors: Nidhal K. El Abbadi, Elaf J. Al Taee
10.5120/17523-8088

Nidhal K. El Abbadi, Elaf J. Al Taee . Breast Cancer Diagnosis by CAD. International Journal of Computer Applications. 100, 5 ( August 2014), 25-29. DOI=10.5120/17523-8088

@article{ 10.5120/17523-8088,
author = { Nidhal K. El Abbadi, Elaf J. Al Taee },
title = { Breast Cancer Diagnosis by CAD },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 5 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 25-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number5/17523-8088/ },
doi = { 10.5120/17523-8088 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:11.946996+05:30
%A Nidhal K. El Abbadi
%A Elaf J. Al Taee
%T Breast Cancer Diagnosis by CAD
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 5
%P 25-29
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death of female worldwide. Mammogram is one of the most excellent technologies currently being used for diagnosing breast cancer. Computer aided diagnosis helps the radiologists to detect abnormalities earlier than traditional procedures. In this paper, we suggested to use some of features selected to distinguish the benign and malignant breast cancer. Tumor segmented and denoising prior to classification. The accuracy of proposed system was 100%.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Breast Cancer Mammography Denoising Diagnosis Image Features.

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