Deep-learning-based projection-domain breast thickness estimation for shape-prior iterative image reconstruction in digital breast tomosynthesis.

Journal: Medical physics
Published Date:

Abstract

BACKGROUND: Digital breast tomosynthesis (DBT) is a technique that can overcome the shortcomings of conventional X-ray mammography and can be effective for the early screening of breast cancer. The compression of the breast is essential during the DBT imaging. However, since the periphery of the breast cannot be compressed to a constant value, nonuniformity of thickness and in-plane shape variation happen. These cause inconvenience in diagnosis, scatter correction, and breast density estimation.

Authors

  • Seoyoung Lee
    Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
  • Hyeongseok Kim
    KAIST Institute for Artificial Intelligence, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
  • Hoyeon Lee
    Department of Radiation Oncology, Massachusetts General Hospital, Massachusetts, Boston, USA.
  • Seungryong Cho