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Reseach Article

Classification of Microcalcification in Digital Mammogram using Stochastic Neighbor Embedding and KNN Classifier

Published on January 2013 by S. Mohan Kumar, G. Balakrishnan
Emerging Technology Trends on Advanced Engineering Research - 2012
Foundation of Computer Science USA
ICETT - Number 1
January 2013
Authors: S. Mohan Kumar, G. Balakrishnan
2cad5108-7658-41f2-8a21-da6fb2281a81

S. Mohan Kumar, G. Balakrishnan . Classification of Microcalcification in Digital Mammogram using Stochastic Neighbor Embedding and KNN Classifier. Emerging Technology Trends on Advanced Engineering Research - 2012. ICETT, 1 (January 2013), 5-9.

@article{
author = { S. Mohan Kumar, G. Balakrishnan },
title = { Classification of Microcalcification in Digital Mammogram using Stochastic Neighbor Embedding and KNN Classifier },
journal = { Emerging Technology Trends on Advanced Engineering Research - 2012 },
issue_date = { January 2013 },
volume = { ICETT },
number = { 1 },
month = { January },
year = { 2013 },
issn = 0975-8887,
pages = { 5-9 },
numpages = 5,
url = { /proceedings/icett/number1/9824-1002/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Emerging Technology Trends on Advanced Engineering Research - 2012
%A S. Mohan Kumar
%A G. Balakrishnan
%T Classification of Microcalcification in Digital Mammogram using Stochastic Neighbor Embedding and KNN Classifier
%J Emerging Technology Trends on Advanced Engineering Research - 2012
%@ 0975-8887
%V ICETT
%N 1
%P 5-9
%D 2013
%I International Journal of Computer Applications
Abstract

Breast cancer has become a common health problem in developed and developing countries during the last decades and also the leading cause of mortality in women each year. Mammogram is a special x-ray examination of the breast made with specific x-ray equipment that can often find tumors too small to be felt. In this paper, the classification of microcalcification in digital mammogram is achieved by using Stochastic Neighbor Embedding (SNE) for reducing high dimensionality data into relatively low dimensional data and K-Nearest Neighbor (KNN) Classifier. This system classifies the mammogram images into normal or abnormal, and the abnormal severity into benign or malignant. Mammography Image Analysis society (MIAS) database is used to evaluate the proposed system. The experiments demonstrate that the proposed method can provide better classification rate.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Stochastic Neighbor Embedding K-nearest Neighbor Digital Mammograms Microcalcifications