Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of medicine including ophthalmology. These methods continue to provide reliable and standardized large scale screening of various image modalities to assist clinicians in identifying diseases. Since optic disc is the most important part of retinal fundus image for glaucoma detection, this paper proposes a two-stage framework that first detects and localizes optic disc and then classifies it into healthy or glaucomatous.

Authors

  • Muhammad Naseer Bajwa
    Fachbereich Informatik, Technische Universität Kaiserslautern, 67663, Kaiserslautern, Germany. bajwa@dfki.uni-kl.de.
  • Muhammad Imran Malik
    Deep Learning Laboratory, National Center of Artificial Intelligence, Islamabad, 46000, Pakistan.
  • Shoaib Ahmed Siddiqui
    Fachbereich Informatik, Technische Universität Kaiserslautern, 67663, Kaiserslautern, Germany.
  • Andreas Dengel
    German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germnay. Andreas.Dengel@dfki.de.
  • Faisal Shafait
    Deep Learning Laboratory, National Center of Artificial Intelligence, Islamabad, 46000, Pakistan.
  • Wolfgang Neumeier
    Ophthalmology Clinic, Rittersberg 9, 67657, Kaiserslautern, Germany.
  • Sheraz Ahmed
    German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germnay. Sheraz.Ahmed@dfki.de.