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

Mohammad Tariqul Islam, Ferdaus Ahmed, Mowafa Househ, Tanvir Alam*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationHealthcare Transformation with Informatics and Artificial Intelligence
EditorsJohn Mantas, Parisis Gallos, Emmanouil Zoulias, Arie Hasman, Mowafa S. Househ, Martha Charalampidou, Andriana Magdalinou
PublisherIOS Press BV
Pages624-627
Number of pages4
ISBN (Electronic)9781643684000
DOIs
Publication statusPublished - 29 Jun 2023
Event21st International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2023 - Athens, Greece
Duration: 1 Jul 20233 Jul 2023

Publication series

NameStudies in Health Technology and Informatics
Volume305
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference21st International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2023
Country/TerritoryGreece
CityAthens
Period1/07/233/07/23

Keywords

  • Fovea
  • Optic Disc
  • Qatar Biobank
  • Retina

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