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Automatic Identification and Elimination of Pectoral Muscle in Digital Mammograms

by K. Vaidehi, T. S. Subashini
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 75 - Number 14
Year of Publication: 2013
Authors: K. Vaidehi, T. S. Subashini
10.5120/13179-0784

K. Vaidehi, T. S. Subashini . Automatic Identification and Elimination of Pectoral Muscle in Digital Mammograms. International Journal of Computer Applications. 75, 14 ( August 2013), 15-18. DOI=10.5120/13179-0784

@article{ 10.5120/13179-0784,
author = { K. Vaidehi, T. S. Subashini },
title = { Automatic Identification and Elimination of Pectoral Muscle in Digital Mammograms },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 75 },
number = { 14 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 15-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume75/number14/13179-0784/ },
doi = { 10.5120/13179-0784 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:44:15.933582+05:30
%A K. Vaidehi
%A T. S. Subashini
%T Automatic Identification and Elimination of Pectoral Muscle in Digital Mammograms
%J International Journal of Computer Applications
%@ 0975-8887
%V 75
%N 14
%P 15-18
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Computer aided detection/diagnosis aims at assisting radiologist in the analysis of digital mammograms. Digital mammogram has emerged as the most popular screening technique for early detection of breast cancer and other abnormalities in human breast tissue. The pectoral muscle represents a predominant density region in most mammograms and can affect/bias the results of image processing methods. This paper addresses the problem of eliminating the pectoral muscles from the mammogram so that further processing for detection and diagnosis of breast cancer is confined to the breast region alone. The proposed work is done in three steps. In the first step, the mammogram is oriented to the left to minimize computations. In the second step the top left quadrant of the mammogram which contains the pectoral muscle is extracted. Next, the pectoral muscle contour is computed using our proposed algorithm. Totally 120 mammogram images were taken up for the study. A comprehensive comparison with manually-drawn contours by the radiologist reveals the strength of the proposed method and shows that it can be effectively used as a preprocessing step in the design of CAD system for breast cancer.

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Index Terms

Computer Science
Information Sciences

Keywords

Pectoral Muscle Digital Mammograms CAD