Efficient Detection and Early Diagnosis of Breast Cancer Using Deep Learning

Abstract

AComputer-aided diagnosis system based on mammograms enables early breast cancer detection, diagnosis and treatment. However, the accuracy of the existing CAD system remains unsatisfactory. In the proposed system, design of critical and early breast cancer detection is done using machine learning approach to make the system detect the tumor cells automatically using advanced image processing techniques. Images pre-processed by studying various parameter extraction such as  color conversion, resizing and filtering. Fuzzy c-means clustering segmentation is carried out by segmentation algorithms. This helps to identify the amount of lesions scattered over the body. Feature extraction is by GLCM and finally, Approximate reasoning method to recognize the tumor shape and position in MRI image using LDA algorithm classification method. Finally the message box will be displayed whether it is benign or malignant.