An approach towards automatic detection of toxoplasmosis using fundus images

Adithi Deborah Chakravarthy, Dilanga Abeyrathna, Mahadevan Subramaniam, Parvathi Chundi, Muhammad Sohail Halim, Murat Hasanreisoglu, Yasir J. Sepah, Quan Dong Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Ocular Toxoplasmosis (OT) is a widespread infectious chorioretinal disease whose timely diagnosis and treatment are crucial to prevent potential vision loss. Diagnosing OT is a challenging task ranging from tedious analyses of fundus images of the eye to serological clinical tests. An automated approach using convolutional neural networks (CNNs) towards diagnosing OT by analyzing fundus images is described. Fundus images are segmented to patches using a sliding window and are classified into healthy and unhealthy fundus image patches using a CNN model. An OT lesion heat map of a fundus image is generated from these patches. The heat map and patch features are then combined to develop a dual input hybrid CNN model detecting OT fundus images with high accuracy. The approach was applied to a dataset of fundus images involving OT and normal subjects and was highly effective in identifying fundus images having OT lesions.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages710-717
Number of pages8
ISBN (Electronic)9781728146171
DOIs
StatePublished - Oct 2019
Event19th International Conference on Bioinformatics and Bioengineering, BIBE 2019 - Athens, Greece
Duration: Oct 28 2019Oct 30 2019

Publication series

NameProceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019

Conference

Conference19th International Conference on Bioinformatics and Bioengineering, BIBE 2019
CountryGreece
CityAthens
Period10/28/1910/30/19

Keywords

  • Deep Learning
  • Medical Imaging
  • Neural Networks
  • Ocular Toxoplasmosis

ASJC Scopus subject areas

  • Information Systems
  • Biomedical Engineering
  • Health Informatics

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