Classification of Benign and Maligant using Deep Learning Technique

Classification of Benign and Maligant using Deep Learning Technique

                        K.Vishnavi1       M.Mahendra2              I.sonia3             M.Karthik4

1,2,3,4ECE, RVRJCCE, INDIA

E-mail: vyshnavikaku@gmail.com1

E-mail: munthamahendrasai@gmail.com2

E-mail: soniaimmadi123@gmail.com3

E-mail: macherlakarthik99 @gmail.com4

Abstract

 Breast cancer is one of the most common malignant tumors in women, which seriously affect women's physical and mental health and even threat to life. At present, microscopic images are the important criterion for doctors to diagnose breast cancer. However, due to the complex structure of microscopic images, it is relatively difficult for doctors to identify breast cancer features. Deep learning is the most mainstream image classification algorithm which uses Convolutional Neural Network (CNN). In this project first, the BreakHis400x (Breast Cancer Histopathological Images)   images will undergo pre-processing such as enhancement and data augmentation in order to increase the number of images. Secondly, the pre-processed dataset will be trained on deep learning model that extracts the features and generate the performance evaluation metric of CNN models. We are going to use python software for classifying the images.