Classification of Breast Cancer Using Ensemble Empirical Mode Decomposition and Autoencoder-Based Methods

Abstract

Considering that breast cancer has been one of the most common diseases in recent years, its early diagnosis and recognition can be effective in its treatment. Image processing techniques are effective methods in diagnosing breast cancer patients. In this method, mammography images are analyzed using image processing techniques and algorithms based on them. Image enhancement and segmentation are done by the density-based method. Analysis by ensemble empirical mode decomposition (EEMD) and feature extraction by autoencoder are the most important elements of the proposed method. Finally, by the boosting class, it is classified into images. The results show that the accuracy of the proposed method is 92.42, which is much better than other compared methods.