Identification and Prediction of Metastatic Tumor in Breast Using Deep Learning Techniques

Abstract

Abstract: Our work aims to develop a system for breast cancer detection using Image Processing Techniques. It addresses the limitations of mammography, such as painful procedures, by introducing thermal image analysis. For mammogram analysis, morphology techniques are applied to enhance the images before feature extraction. The preprocessed image used to classify mammograms into threecategories: Normal Fatty Breast, Abnormal Fatty Breast, and Glandular Breast. In the case of thermal images, the system analyses the distribution of heat around the breast. Variations in heat levels are used to identify potential cancerous areas. Additionally, the project includes the development of a user-friendly Graphical User Interface (GUI) to enhance accessibility for users. The proposed system provides option on architectures namely CNN, VGG16 and Densenet121 using which the result is obtained.