Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective
Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective is a scholarly work, published in 2017 in ''Journal of Digital Imaging''. The main subjects of the publication include BI-RADS, radiology, medicine, artificial intelligence, breast cancer screening, leverage, computer science, cancer epidemiology, medical imaging, breast imaging, breast cancer, convolutional neural network, deep learning, medical physics, and mammography. The authors implemented a convolutional neural network (CNN)-based deep learning model, aimed at distinguishing the breast density categories using a large (15,415 images) set of real-world clinical mammogram images.