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Reseach Article

Implementation of Neural Network for Cancer Diagnosis

Published on November 2011 by Devesh D. Nawgaje, Dr. Rajendra D.Kanphade
2nd National Conference on Information and Communication Technology
Foundation of Computer Science USA
NCICT - Number 3
November 2011
Authors: Devesh D. Nawgaje, Dr. Rajendra D.Kanphade
e77b3ee3-7efc-41c1-b69b-3012a47a7c8d

Devesh D. Nawgaje, Dr. Rajendra D.Kanphade . Implementation of Neural Network for Cancer Diagnosis. 2nd National Conference on Information and Communication Technology. NCICT, 3 (November 2011), 19-24.

@article{
author = { Devesh D. Nawgaje, Dr. Rajendra D.Kanphade },
title = { Implementation of Neural Network for Cancer Diagnosis },
journal = { 2nd National Conference on Information and Communication Technology },
issue_date = { November 2011 },
volume = { NCICT },
number = { 3 },
month = { November },
year = { 2011 },
issn = 0975-8887,
pages = { 19-24 },
numpages = 6,
url = { /proceedings/ncict/number3/4290-ncict020/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 2nd National Conference on Information and Communication Technology
%A Devesh D. Nawgaje
%A Dr. Rajendra D.Kanphade
%T Implementation of Neural Network for Cancer Diagnosis
%J 2nd National Conference on Information and Communication Technology
%@ 0975-8887
%V NCICT
%N 3
%P 19-24
%D 2011
%I International Journal of Computer Applications
Abstract

Cancer is the term used for diseases in which abnormal cells divide without control and are able to invade other tissues. There are more than hundred different types of cancer, one of them being Breast Cancer. Percentage of population, dying due to this type of cancer or due to incorrect diagnosis is very high. This invokes the idea of use of some Artificial Intelligence techniques for detection of this type of cancer. One technical approach is to use Image Processing as initial step in detecting, followed by suitable artificial intelligent techniques. Image processing basically involves number of processes, out of which feature extraction satisfied our need. Some of the Image Processing parameters have been extracted from mammographic images using MATLAB. These parameters served as input for training Neural-Network. An unknown image was then taken to test the trained system.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Breast cancer classification digital mammograms microcalcification neural networks