Mammography Image Quality Assurance Using Deep Learning.

Journal: IEEE transactions on bio-medical engineering
Published Date:

Abstract

OBJECTIVE: According to the European Reference Organization for Quality Assured Breast Cancer Screening and Diagnostic Services (EUREF) image quality in mammography is assessed by recording and analyzing a set of images of the CDMAM phantom. The EUREF procedure applies an automated analysis combining image registration, signal detection and nonlinear fitting. We present a proof of concept for an end-to-end deep learning framework that assesses image quality on the basis of single images as an alternative.

Authors

  • Tobias Kretz
  • Klaus-Robert Mueller
  • Tobias Schaeffter
  • Clemens Elster