MultiHeadGAN: A deep learning method for low contrast retinal pigment epithelium cell segmentation with fluorescent flatmount microscopy images.

Journal: Computers in biology and medicine
Published Date:

Abstract

BACKGROUND: Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE aging is accompanied by changes in cell morphological features, an accurate segmentation of RPE cells is a prerequisite to such morphology analyses. Due the overwhelmingly large cell number, manual annotations of RPE cell borders are time-consuming. Computer based methods do not work well on cells with weak or missing borders in the impaired RPE sheet regions.

Authors

  • Hanyi Yu
    Department of Computer Science, Emory University, Atlanta, 30322, GA, USA. Electronic address: hyu88@emory.edu.
  • Fusheng Wang
    Stony Brook University, Stony Brook, NY.
  • George Teodoro
    Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG, 31270, USA.
  • John Nickerson
    Department of Ophthalmology, Emory University, Atlanta, 30322, GA, USA. Electronic address: litjn@emory.edu.
  • Jun Kong
    Stony Brook University, Stony Brook, NY.