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Efficient Early Detection of Breast Cancer Detection using ANN and DWT

Parvati N. Angadi, M. Nagendra. Published in Image Processing.

Communications on Applied Electronics
Year of Publication: 2018
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Parvati N. Angadi, M. Nagendra

Parvati N Angadi and M Nagendra. Efficient Early Detection of Breast Cancer Detection using ANN and DWT. Communications on Applied Electronics 7(13):1-6, February 2018. BibTeX

	author = {Parvati N. Angadi and M. Nagendra},
	title = {Efficient Early Detection of Breast Cancer Detection using ANN and DWT},
	journal = {Communications on Applied Electronics},
	issue_date = {February 2018},
	volume = {7},
	number = {13},
	month = {Feb},
	year = {2018},
	issn = {2394-4714},
	pages = {1-6},
	numpages = {6},
	url = {},
	doi = {10.5120/cae2018652745},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Excavating the prior literature shows that there has been an abundant prior studies in the area of breast cancer detection but, very little work has been put towards 'Early Detection of Breast Cancer.' In the country like US, where majority of the women has higher vulnerabilities of becoming a victim of breast cancer, as evident from history, early detection of breast cancer can play a boon in medical science. This paper therefore makes an attempt where the system is designed considering a dataset of mammogram from DDSM where feature extraction is performed using Discrete Wavelet Transform (DWT), and the feature vectors are then efficiently trained by Artificial Neural Network (ANN). The final trained results are stored in matrix and validation is performed using real time mammogram image to exhibit that the proposed model has successfully accomplished more than 90% in accuracy, sensitivity, and specificity.


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Breast Cancer Detection, Artificial Neural Network, Discrete Wavelet Transfor, DDSM