Abstract

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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