Abstract: In this paper, a framework has been presented by using a combination of deep Convolutional Neural Network (CNN) with Support Vector Machine (SVM). Proposed method first perform preprocessing to resize the image so that it can be suitable for CNN and perform enhancement quality of the images can be enhanced. Deep Convolutional Neural Network (CNN) has been used for features extraction and classification with Support Vector Machine (SVM). Standard dataset MIAS and DDMS has been employed for testing the proposed framework by generating new images from these datasets by the process of augmentation. Different performance measures like Accuracy, Sensitivity, Specificity and area under the curve (AUC) has been employed as a quantitative measure and compared with state of the art existing methods. Results shows that proposed framework has attained accuracy 93.35% and 93% sensitivity.

M. Arfan Jaffar, “Deep Learning based Computer Aided Diagnosis System for Breast Mammograms” International Journal of Advanced Computer Science and Applications(IJACSA), 8(7), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080738

@article{Jaffar2017,
title = {Deep Learning based Computer Aided Diagnosis System for Breast Mammograms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080738},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080738},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {7},
author = {M. Arfan Jaffar}
}