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Reseach Article

Methods towards the Classification of Clustered Microcalcification

Published on July 2012 by S. Narasimhamurthy, Arun Kumar, H. S. Sheshadri
Advanced Computing and Communication Technologies for HPC Applications
Foundation of Computer Science USA
ACCTHPCA - Number 3
July 2012
Authors: S. Narasimhamurthy, Arun Kumar, H. S. Sheshadri
af15abe5-a8bf-45a9-a4c1-1fb53a60db81

S. Narasimhamurthy, Arun Kumar, H. S. Sheshadri . Methods towards the Classification of Clustered Microcalcification. Advanced Computing and Communication Technologies for HPC Applications. ACCTHPCA, 3 (July 2012), 35-38.

@article{
author = { S. Narasimhamurthy, Arun Kumar, H. S. Sheshadri },
title = { Methods towards the Classification of Clustered Microcalcification },
journal = { Advanced Computing and Communication Technologies for HPC Applications },
issue_date = { July 2012 },
volume = { ACCTHPCA },
number = { 3 },
month = { July },
year = { 2012 },
issn = 0975-8887,
pages = { 35-38 },
numpages = 4,
url = { /specialissues/accthpca/number3/7570-1024/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Advanced Computing and Communication Technologies for HPC Applications
%A S. Narasimhamurthy
%A Arun Kumar
%A H. S. Sheshadri
%T Methods towards the Classification of Clustered Microcalcification
%J Advanced Computing and Communication Technologies for HPC Applications
%@ 0975-8887
%V ACCTHPCA
%N 3
%P 35-38
%D 2012
%I International Journal of Computer Applications
Abstract

Breast cancer is one of the leading causes of death among the women. Mammogram analysis is the most effective method that helps in the early detection of breast cancer. Microcalcification, masses, and architectural detection in the mammogram plays an important role in the later stages of diagnosis. In this paper we propose an effective method for the detection and classification of clustered microcalcification. We applied the proposed method in the MIAS datasets and found the effectiveness in the detection and classification of clustered microcalcification. We also brief out in this article the methods adopted to select the features for clustered microcalcification and technique to handle the class imbalance specific to microcalcification classification problem.

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Index Terms

Computer Science
Information Sciences

Keywords

Classification Clustered Microcalcification Imbalanced Data Sets Mammography