Angular super-resolution in X-ray projection radiography using deep neural network: Implementation on rotational angiography.

Journal: Biomedical journal
Published Date:

Abstract

BACKGROUND: Rotational angiography acquires radiographs at multiple projection angles to demonstrate superimposed vasculature. However, this comes at the expense of the inherent risk of increased ionizing radiation. In this paper, building upon a successful deep learning model, we developed a novel technique to super-resolve the radiography at different projection angles to reduce the actual projections needed for a diagnosable radiographic procedure.

Authors

  • Tiing Yee Siow
    Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan.
  • Cheng-Yu Ma
    Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
  • Cheng Hong Toh
    Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan. Electronic address: eldomtoh@hotmail.com.