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Reseach Article

Cloud based Decision Support System for Diagnosis of Breast Cancer using Digital Mammograms

Published on December 2012 by S. Aruna, L. V. Nandakishore, S. P. Rajagopalan
EGovernance and Cloud Computing Services - 2012
Foundation of Computer Science USA
EGOV - Number 1
December 2012
Authors: S. Aruna, L. V. Nandakishore, S. P. Rajagopalan
3424eef2-ae40-4d45-85af-c987fe5451b9

S. Aruna, L. V. Nandakishore, S. P. Rajagopalan . Cloud based Decision Support System for Diagnosis of Breast Cancer using Digital Mammograms. EGovernance and Cloud Computing Services - 2012. EGOV, 1 (December 2012), 1-3.

@article{
author = { S. Aruna, L. V. Nandakishore, S. P. Rajagopalan },
title = { Cloud based Decision Support System for Diagnosis of Breast Cancer using Digital Mammograms },
journal = { EGovernance and Cloud Computing Services - 2012 },
issue_date = { December 2012 },
volume = { EGOV },
number = { 1 },
month = { December },
year = { 2012 },
issn = 0975-8887,
pages = { 1-3 },
numpages = 3,
url = { /proceedings/egov/number1/9480-1002/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 EGovernance and Cloud Computing Services - 2012
%A S. Aruna
%A L. V. Nandakishore
%A S. P. Rajagopalan
%T Cloud based Decision Support System for Diagnosis of Breast Cancer using Digital Mammograms
%J EGovernance and Cloud Computing Services - 2012
%@ 0975-8887
%V EGOV
%N 1
%P 1-3
%D 2012
%I International Journal of Computer Applications
Abstract

In this paper, we propose a cloud based decision support system for screening breast cancer using digital mammograms. The proposed system is deployed in a private cloud as software / infrastructure as a service. The combination of image enhancement techniques, feature extraction techniques, feature selection techniques, ensemble neural networks for classification, results verification process and deployment in the private cloud are added advantages for effective performance of the system.

References
  1. Breast Cancer What Are the Key Statistics for Breast Cancer?. American Cancer Society Cancer Resource Information. http://www. cancer. org
  2. Harirchi, et al. , ¯Breast cancer in Iran: a review of 903 case records,. Public Health, 2000. 114(2): p. 143-145.
  3. Subashini. T, Ramalingam. V, Palanivel. S, 2009, ¯Breast mass classification based on cytological patterns using RBFNN and SVM,. Expert Systems with Applications, 36(3): p. 5284-5290.
  4. Sariego J, 2010. "Breast cancer in the young patient". The American surgeon, 76 (12), pp 1397–1401
  5. Kekre HB, Sarode Tanuja K and Gharge Saylee M, 2009, "Tumor Detection in Mammography Images using Vector Quantization Technique", International Journal of Intelligent Information Technology Application, 2(5):237-242.
  6. Baines CJ, McFarlane DV, Miller AB, 1990, "The role of the reference radiologist: Estimates of interobserver agreement and potential delay in cancer detection in the national screening study". Invest Radiol, 25: 971-076.
Index Terms

Computer Science
Information Sciences

Keywords

Breast Cancer Digital Mammograms Neural Networks Ada Boost Feature Extraction Feature Selection Cloud Computing