SEQUENTIAL CONVOLUTIONAL NEURAL NETWORK FOR AUTOMATIC BREAST CANCER IMAGE CLASSIFICATION USING HISTOPATHOLOGICAL IMAGES
Ritu Tandon, Shweta Agrawal, Parag Goyal · Journal of Critical Reviews · 2020
Breast cancer is the major cause of death among the women in all over the world and detection of breast cancer at early or initial stage can increase the survival rate of the patient. Malignancy of the cells of breast tissue is detected for diagnosing the breast cancer. Now days various image processing techniques are used to analyze the histopathological images for diagnosing the cancer. Manual detection of these cells is very time consuming and the result will depend upon the experience of the pathologist. So computer aided techniques are used for fast processing and accurate result of the diagnosis. The Deep learning model uses the Convolutional neural network (CNN) that automatically extracts the features and classify the image using fully connected network. In this paper, we have trained a Sequential convolutional neural network and obtained the highest prediction accuracy for detection of breast cancer up to 99.61%.