Abstract:
Breast Cancer detection with mammography, which is a critical task in medical imaging serves
as a primary screening tool. Deep Learning techniques have shown significant improvement in
recent years for improving efficiency and accuracy in Breast Cancer detection from
mammograms. Our project has proposed a deep leaning model for breast cancer detection using
mammogram images by deploying Convolutional Neural Networks (CNN) for feature
extraction and Image classification. The model has been trained on large number of datasets
containing mammogram images which have been annotated by the expert Radiologists.
Experimental results show the accuracy and effectiveness of our model by detecting
abnormalities in the respective regions of mammogram images which are indicators of Breast
Cancer. This method has shown significantly improved performance as compared to traditional
methods of Breast cancer detection. The proposed methodology has shown importance in the
medical field by aiding radiologists in early detection and diagnosis and ultimately improving
patient outcomes.
