Breast Cancer Detection Using Extreme Learning Machine Based on Feature Fusion With CNN Deep Features

作者：Zhiqiong Wang, Mo Li, Huaxia Wang, Hanyu Jiang, Yudong Yao, Hao Zhang, Junchang Xin · 发表于：IEEE Access · 年份：2019 · DOI：10.1109/access.2019.2892795 · 被引用次数：350 · 研究领域：Machine Learning and ELM、AI in cancer detection、Face and Expression Recognition

A computer-aided diagnosis (CAD) system based on mammograms enables early breast cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD systems remains unsatisfactory. This paper explores a breast CAD method based on feature fusion with convolutional neural network (CNN) deep features. First, we propose a mass detection method based on CNN deep features and unsupervised extreme learning machine (ELM) clustering. Second, we build a feature set fusing deep features, morphological features, texture features, and density features. Third, an ELM classifier is developed using the fused feature set to classify benign and malignant breast masses. Extensive experiments demonstrate the accuracy and efficiency of our proposed mass detection and breast cancer classification method.