Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: With the growing adoption of digital breast tomosynthesis (DBT) in breast cancer screening, we compare the performance of deep learning computer-aided diagnosis on DBT images to that of conventional full-field digital mammography (FFDM).

Authors

  • Kayla Mendel
    The University of Chicago, 5801 S Ellis Ave, Chicago, Illinois. Electronic address: kmendel@uchicago.edu.
  • Hui Li
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Deepa Sheth
    The University of Chicago, 5801 S Ellis Ave, Chicago, Illinois.
  • Maryellen Giger
    The University of Chicago, 5801 S Ellis Ave, Chicago, Illinois.