Effective Breast Cancer Classification Using SDNN Based E-Health Care Services Framework

In the modern environment, many health care issues are raised day by day. Detecting the early stage of breast cancer may lead to prevention. In this paper, we proposed the breast cancer classification of the E-health care services framework with the Internet of Medical Things by utilizing the support value-based Deep Neural Network (SDNN) classification. Initially, the input cytology images are taken from the local health care center, and then attain the process of pre-processing and filtering technique is used the noise removed image goes to the feature extraction process includes entropy, Geometrical features, Textural features. After that segmentation is done using Histo-sigmoid fuzzy clustering. Finally, it attains the classification process of the proposed SDNN support value-based deep neural network. SDNN classifier classifies the breast cancer images as normal or abnormal compared with the existing approaches. The proposed method accuracy is 97.4 % which is better than other state - of - the art methods.