Computer-aided Breast Cancer Diagnosis using Deep Convolutional Neural Networks
Anushka Singhania, Anu Narera, Ritu Rani, Amita Dev, Poonam Bansal, Arun Sharma · 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · 2022
In the contemporary period, breast cancer has become one of the leading causes of cancer-related mortality globally. It is referred to as asymptomatic cancer because it has no symptoms at all when it is first diagnosed. As a result, radiology professionals periodically evaluate mammograms to check for unusual lesions and pinpoint the location, kind, and shape of any troublesome breast areas. For the segmentation and detection of breast cancers, image analysis techniques are vital because they can accurately depict key morphological features that are necessary for a conclusive diagnosis. This paper presents the image segmentation of a breast tumour using U-Net model. The proposed model attained a high accuracy of 94.29% on our training dataset. The complete empirical analysis along with the exhaustive literature review is presented in the paper.