Fully automated CADx for early breast cancer detection using image processing and machine learning

Breast cancer accounts for 16% of all cancers among females. Current early detection methods are expensive or computationally complex and thus unsuitable for developing countries. For this reason, a real-time fully automated Computer Aided Diagnosis system for Breast Cancer early detection from Ultrasound images is built in this paper. The proposed and implemented design comprises into its modules state of the art techniques and methods. The implemented design includes preprocessing/filtering of the input ultrasound image, segmentation of the region of interest from the background image and feature set calculation/extraction. Machine learning algorithms were implemented for classification of the tumour. Successful implementation with satisfactory run time is achieved with a final accuracy improved by 10% from previous work using the same set of features. Additional evaluation metrics like precision-recall plots and confusion matrices were also used to test and evaluate the system overall balanced performance.