Automated Breast Cancer Detection in Digital Mammograms of Various Densities via Deep Learning.

ABSTRACT: Mammography plays an important role in screening breast cancer among females, and artificial intelligence has enabled the automated detection of diseases on medical images. This study aimed to develop a deep learning model detecting breast cancer in digital mammograms of various densities and to evaluate the model performance compared to previous studies. From 1501 subjects who underwent digital mammography between February 2007 and May 2015, craniocaudal and mediolateral view mammograms were included and concatenated for each breast, ultimately producing 3002 merged images. Two convolutional neural networks were trained to detect any malignant lesion on the merged images. The performances were tested using 301 merged images from 284 subjects and compared to a meta-analysis including 12 pr

SUBMITTER: Suh YJ 

PROVIDER: S-EPMC7711783 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature