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Breast Cancer Detection Using Neural Network

S.Nadiger 1 , A.Dixit 2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 793-797, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.793797

Online published on Jul 31, 2018

Copyright © S.Nadiger, A.Dixit . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S.Nadiger, A.Dixit, “Breast Cancer Detection Using Neural Network,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.793-797, 2018.

MLA Style Citation: S.Nadiger, A.Dixit "Breast Cancer Detection Using Neural Network." International Journal of Computer Sciences and Engineering 6.7 (2018): 793-797.

APA Style Citation: S.Nadiger, A.Dixit, (2018). Breast Cancer Detection Using Neural Network. International Journal of Computer Sciences and Engineering, 6(7), 793-797.

BibTex Style Citation:
@article{_2018,
author = {S.Nadiger, A.Dixit},
title = {Breast Cancer Detection Using Neural Network},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {793-797},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2513},
doi = {https://doi.org/10.26438/ijcse/v6i7.793797}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.793797}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2513
TI - Breast Cancer Detection Using Neural Network
T2 - International Journal of Computer Sciences and Engineering
AU - S.Nadiger, A.Dixit
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 793-797
IS - 7
VL - 6
SN - 2347-2693
ER -

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Abstract

The aim of this project is to detect breast cancer by extracting the features of the affected tumour. Classification of the cancer cells is done with neural networks. The project consists of three phases namely, pre processing, feature extraction and classification. Pre processing is done using median filter; the features are extracted from digital mammogram which includes position, texture and shape. The features are trained by neural networks to classify the cancer cells. Maximum likely hood estimation is used to calculate the area affected to determine the depth of tumour. In this paper artificial neural network are used to develop a system for diagnosis, prognosis and prediction of breast cancer. Breast cancer is a type of cancer originating from breast tissues, and most commonly this is originated from the inner lining of milk ducts. Breast cancer occurs in human and other mamma is also. Cardiology, radiology, oncology, urology are currently the burning areas in medical sciences in which neural networks are currently progressing on.

Key-Words / Index Term

Breastcancer,malign,benign,MLE,Pre-Processing,DWT,Digitalimageprocessing

References

[1]A.Jemal, F.Bray, M.M.Canter, J.Feraly. et.al, “Global cancer statistics,” A cancer journal for clinicians, 2011.
[2] A.Malich, D.R.Fischer and J.B.Ottocher, “CAD for mammography: the technique, results, current role and further developments,” European radiology, 2006.
[3] K.Kelley, J.Dean, W.Comulada.et.al, “Breast cancer detection using automated whole ultrasound and mammography in radio graphically dense breasts,” European Radiology, vol.20, pp.734-742, 2010.
[4] M.B.Dillencourt, H.Samet and M.Tammien, “A general approach to connect-component labelling for arbitrary image representation”.
[5] N.F.Boyd, H.Guo, L.J.Martin, L.Sun, J.Stone , E.Fishell.et.al,2007.