An Automatic Detection of Breast Cancer Based On Deep Learning Using Long Short-Term Memory Classifier

This project proposes an automatic detection of breast cancer diagnosis and prognosis based on deep learning using Long Short-term Memory classifier. To reduce the noises in the image, the Adaptive filter is employed at the pre-processing stage. The pre-processed image is segmented by Fuzzy C-means (FCM) segmentation algorithm for active partition of image. The segmented features are extracted by Gray Level Co-occurrence Matrix Method, in which all the essential features are extracted for enhanced classification. An effective classifier, LSTM Classifier is used and final results are predicted. By using LSTM Classifier, the obtained results were accurate. This project is implemented with MATLAB simulation software and the output reveals the classification accuracy.