Title: Identification of Glaucoma from Fundus Images Using Deep Learning Techniques – A literature Review


Authors:

Nidhi Srivastav

nidhi@skit.ac.in
Department of Computer Science Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur-302017 (India),

Sandeep Singh

sandeepsingh18300@gmail.com
Department of Computer Science Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur-302017 (India)

Pages: 12-19

DOI:

Abstract:

Glaucoma, a leading cause of irreversible blindness worldwide, necessitates early and accurate diagnosis to prevent significant vision loss. Recent advancements in deep learning have revolutionized medical imaging, offering promising tools for automated glaucoma detection from fundus images. This review paper provides a comprehensive overview of the current state-of-the-art deep learning techniques for glaucoma identification, summarizing various methodologies, datasets, performance metrics, and highlighting the challenges and future directions in this domain.

Keywords: