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Content-based retrieval of retinal images for maculopathy

Authors:

Gopal Datt Joshi,

Jayanthi SivaswamyAuthors Info & Claims

IHI '10: Proceedings of the 1st ACM International Health Informatics Symposium

Pages 135 - 143

https://doi.org/10.1145/1882992.1883013

Published: 11 November 2010 Publication History

Abstract

A growing number of public initiatives for screening the population for retinal disorders along with widespread availability of digital fundus (retina) cameras is leading to large accumulation of color fundus images. The ability to retrieve images based on pathologic state is a powerful functionality that has wide applications in evidence-based medicine, automated computer assisted diagnosis and in training ophthalmologists. In this paper, we propose a new methodology for content-based retrieval of retinal images showing symptoms of maculopathy. Taking the view of a disease region as one which exhibits deviation from the normal image background, a model for the image background is learnt and used to extract disease-affected image regions. These are then analysed to assess the severity level of maculopathy. Symmetry-based descriptor is derived for the macula region and employed for retrieval of images according to severity of maculopathy. The proposed approach has been tested on a publicly available dataset. The results show that background learning is successful as images with or no maculopathy are detected with a mean precision of 0.98. An aggregate precision of 0.89 is achieved for retrieval of images at three severity-levels of macular edema, demonstrating the potential offered by the proposed disease-based retrieval system.

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Cited By

Pavithra KKumar PGeetha MBhandary S(2023)Computer aided diagnosis of diabetic macular edema in retinal fundus and OCT images: A reviewBiocybernetics and Biomedical Engineering10.1016/j.bbe.2022.12.00543:1(157-188)Online publication date: Jan-2023
https://doi.org/10.1016/j.bbe.2022.12.005
Medhi JDandapat S(2016)Improved analysis of Diabetic Maculopathy using level set spatial fuzzy clustering2016 Twenty Second National Conference on Communication (NCC)10.1109/NCC.2016.7561198(1-6)Online publication date: Mar-2016
https://doi.org/10.1109/NCC.2016.7561198
van Grinsven MChakravarty ASivaswamy JTheelen Tvan Ginneken BSanchez C(2013)A Bag of Words approach for discriminating between retinal images containing exudates or drusen2013 IEEE 10th International Symposium on Biomedical Imaging10.1109/ISBI.2013.6556806(1444-1447)Online publication date: Apr-2013
https://doi.org/10.1109/ISBI.2013.6556806
Show More Cited By

Index Terms

Content-based retrieval of retinal images for maculopathy
1. Information systems
  1. Information retrieval
    1. Document representation

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Published In

cover image ACM Other conferences

IHI '10: Proceedings of the 1st ACM International Health Informatics Symposium

November 2010

886 pages

ISBN:9781450300308

DOI:10.1145/1882992

Editor:
Tiffany Veinot
University of Michigan, USA
,
General Chairs:
Ümit V. Çatalyürek
The Ohio State University, USA
,
Gang Luo
IBM Research, USA
,
Program Chairs:
Henrique Andrade
Goldman Sachs, USA
,
Neil R. Smalheiser
University of Illinois, Chicago, USA

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGHIT: ACM Special Interest Group on Health Informatics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 November 2010

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IHI '10

IHI '10: ACM International Health Informatics Symposium

November 11 - 12, 2010

Virginia, Arlington, USA

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Cited By

Pavithra KKumar PGeetha MBhandary S(2023)Computer aided diagnosis of diabetic macular edema in retinal fundus and OCT images: A reviewBiocybernetics and Biomedical Engineering10.1016/j.bbe.2022.12.00543:1(157-188)Online publication date: Jan-2023
https://doi.org/10.1016/j.bbe.2022.12.005
Medhi JDandapat S(2016)Improved analysis of Diabetic Maculopathy using level set spatial fuzzy clustering2016 Twenty Second National Conference on Communication (NCC)10.1109/NCC.2016.7561198(1-6)Online publication date: Mar-2016
https://doi.org/10.1109/NCC.2016.7561198
van Grinsven MChakravarty ASivaswamy JTheelen Tvan Ginneken BSanchez C(2013)A Bag of Words approach for discriminating between retinal images containing exudates or drusen2013 IEEE 10th International Symposium on Biomedical Imaging10.1109/ISBI.2013.6556806(1444-1447)Online publication date: Apr-2013
https://doi.org/10.1109/ISBI.2013.6556806
Naguib AGhanem AFahmy A(2013)Content based image retrieval of diabetic macular edema imagesProceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems10.1109/CBMS.2013.6627877(560-562)Online publication date: Jun-2013
https://doi.org/10.1109/CBMS.2013.6627877
J. SV. N(2013)Analysis of Human Retinal Vasculature for Content Based Image Retrieval ApplicationsProceedings of the 4th International Conference on Swarm, Evolutionary, and Memetic Computing - Volume 829810.1007/978-3-319-03756-1_54(606-616)Online publication date: 19-Dec-2013
https://dl.acm.org/doi/10.1007/978-3-319-03756-1_54
Deepak KSivaswamy J(2012)Automatic assessment of macular edema from color retinal imagesIEEE Transactions on Medical Imaging10.1109/TMI.2011.217885631:3(766-776)Online publication date: Mar-2012
https://doi.org/10.1109/TMI.2011.2178856
Sivakamasundari JKavitha GNatarajan VRamakrishnan S(2012)Content based human retinal image retrieval using vascular feature extractionProceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II10.1007/978-3-642-28490-8_49(468-476)Online publication date: 19-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28490-8_49

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