DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images.

Journal: Translational vision science & technology
Published Date:

Abstract

PURPOSE: To remove blood vessel shadows from optical coherence tomography (OCT) images of the optic nerve head (ONH).

Authors

  • Haris Cheong
    Ophthalmic Engineering and Innovation Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore.
  • Sripad Krishna Devalla
    Ophthalmic Engineering and Innovation Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore.
  • Tan Hung Pham
    Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
  • Liang Zhang
  • Tin Aung Tun
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Xiaofei Wang
    Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
  • Shamira Perera
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
  • Leopold Schmetterer
    Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
  • Tin Aung
    Singapore Eye Research Institute, Singapore National Eye Center, Singapore.
  • Craig Boote
    Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
  • Alexandre Thiery
    Department of Statistics and Applied Probability, National University of Singapore, Singapore.
  • MichaĆ«l J A Girard
    Ophthalmic Engineering and Innovation Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore.