A Deep Learning-Based Approach Towards Simultaneous Localization of Optic Disc and Fovea from Retinal Fundus Images.

Journal: Studies in health technology and informatics
Published Date:

Abstract

In this work, we propose a multi-task learning-based approach towards the localization of optic disc and fovea from human retinal fundus images using a deep learning-based approach. Formulating the task as an image-based regression problem, we propose a Densenet121-based architecture through an extensive set of experiments with a variety of CNN architectures. Our proposed approach achieved an average mean absolute error of only 13pixels (0.04%), mean squared error of 11 pixels (0.005%), and a root mean square error of only 0.02 (13%) on the IDRiD dataset.

Authors

  • Mohammad Tariqul Islam
    Computer Science Department, Southern Connecticut State University, USA.
  • Ferdaus Ahmed
    Infosys Ltd, Texas, USA.
  • Mowafa Househ
    Faculty College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar1.
  • Tanvir Alam
    College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.