Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression.

Journal: IEEE transactions on bio-medical engineering
Published Date: Jun 17, 2021

Abstract

OBJECTIVE: Glaucoma is the second leading cause of blindness worldwide. Glaucomatous progression can be easily monitored by analyzing the degeneration of retinal ganglion cells (RGCs). Many researchers have screened glaucoma by measuring cup-to-disc ratios from fundus and optical coherence tomography scans. However, this paper presents a novel strategy that pays attention to the RGC atrophy for screening glaucomatous pathologies and grading their severity.

Authors

  • Hina Raja
  • Taimur Hassan
    Department of Computer Engineering, National University of Sciences and Technology, Islamabad, Pakistan.
  • Muhammad Usman Akram
    Department of Computer Engineering, College of E&ME, National University of Sciences and Technology, Islamabad, Pakistan.
  • Naoufel Werghi
    Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.

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