Skip to main content

Automated Localization of Optic Disk, Detection of Microaneurysms and Extraction of Blood Vessels to Bypass Angiography

  • Conference paper

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 327))

Abstract

Diabetic Retinopathy is considered as a root cause of vision loss for diabetic patients. For Diabetic patients, regular check-up and screening is required. At times lesions are not visible through fundus image, Dr. Recommends angiography. However Angiography is not advisable in certain conditions like if patient is of very old age, if patient is a pregnant woman, if patient is a child, if patient has some critical disease or if patient has undergone some major surgery. In this paper we propose a system Automated Diabetic Retinopathy Detection System (ADRDS) through which fundus image will be processed in such a way that it will have the similar quality to that of angiogram where lesions are clearly visible. It will also identify the Optic Disk (OD) and extract blood vessels because pattern of these blood vessels near optic disc region plays an important role in diagnosis for eye disease. We have passed 100 images in the system collected from Dr. Manoj Saswade and Dr. Neha Deshpande and got true positive rate of 100%, false positive rate of 3%, and accuracy score is 0.9902.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Silberman, N., et al.: Case for Automated Detection of Diabetic Retinopathy. In: Association for the Advancement of Artificial Intelligence (2010), www.aaai.org

  2. (ROC Curve), http://www.who.int/mediacentre/factsheets/fs312/en/

  3. Patwari, M.B., Manza, R.R., Saswade, M., Deshpande, N.: A Critical Review of Expert Systems for Detection and Diagnosis of Diabetic Retinopathy. Ciit International Journal of Fuzzy Systems (February 2012), DOI: FS022012001 ISSN 0974-9721, 0974-9608 (IF 0.441)

    Google Scholar 

  4. (Angiography), http://www.webmd.com/eye-health/eye-angiogram?page=2

  5. Kanski, J.J.: Clinical Ophthalmology: A Systematic Approach, 3rd edn.

    Google Scholar 

  6. Gonzalez, R.C., Woods, R.E.: Digital Image processing. Pearson Education, New Delhi (2002)

    Google Scholar 

  7. Zhu, X., Rangayyan, R.M., Ells, A.L.: Digital Image Processing for Ophthalmology: Detection of the Optic Nerve Head

    Google Scholar 

  8. Aquino, A., et al.: Automated Optic Disc Detection in Retinal Images of Patients with Diabetic Retinopathy and Risk of Macular Edema. International Journal of Biological and Life Sciences 8(2) (2012)

    Google Scholar 

  9. Rangayyan, R.M., et al.: Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis. Journal of Digital Imaging 23(4), 438–453 (2010)

    Article  Google Scholar 

  10. Rajput, Y.M., Manza, R.R., Patwari, M.B., Deshpande, N.: RetinalOpticDisc Detection Using Speed Up Robust Features. In: National Conference on Computer & Management Science (CMS-2013), RadhaiMahavidyalaya, Auarngabad- 431003(MS) India, April 25-26 (2013)

    Google Scholar 

  11. Jiméneza, S., Alemanya, P., et al.: Automatic detection of vessels in color fundus images. Sociedad Española de Oftalmología (2009)

    Google Scholar 

  12. Reza, A.W., et al.: Diabetic Retinopathy: A Quadtree Based Blood Vessel Detection Algorithm Using RGB Components in Fundus Images. Received: Published by Elsevier España, s.larchsocespoftalmol 85(3), 103–109 (2010), Media, LLC 2007

    Google Scholar 

  13. Vijayachitra, S., et al.: Analysis Of Diabetic Retinopathy Images Using Blood Vessel Extraction. International Journal of Advanced Engineering Research and Studies E-ISSN2249–8974 IJAERS/Vol. I/ Issue II/January-March, 2012/89-91 Research Article (2012)

    Google Scholar 

  14. Rajput, Y.M., Manza, R.R., Patwari, M.B., Deshpande, N.: Third National Conference on Advances in Computing(NCAC-2013). In: Third National Conference on Advances in Computing(NCAC-2013), March 5–6, North Maharashtra University, Jalgaon (2013)

    Google Scholar 

  15. Akram, U.M., et al.: Automated Detection of Dark and Bright Lesions in Retinal Images for Early Detection of Diabetic Retinopathy. In: Received: 1 August 2011 / Accepted: 25 October 2011 / Published online: 17. Springer Science+Business Media, LLC (November 2011)

    Google Scholar 

  16. Poddar, S., et al.: Quantitative Clinical Marker Extraction from Colour Fundus Images for Non-Proliferative Diabetic Retinopathy Grading. In: International Conference on Image Information Processing (2011)

    Google Scholar 

  17. (ICIIP 2011) (ICIIP 2011) 978-1-61284-861-7/11/$26.00 ©2011 IEEE

    Google Scholar 

  18. Singh, N., et al.: Automated Early Detection of Diabetic Retinopathy Using Image Analysis Techniques. International Journal of Computer Applications 8(2), 975–8887 (2010)

    Article  Google Scholar 

  19. (Blood Vessels Diameter), http://www.vassarstats.net/roc1.html

  20. Patwari, M.B., Manza, R.R., Rajput, Y.M., Saswade, M., Deshpande, N.K.: Review on Detection and Classification of Diabetic Retinopathy Lesions Using Image Processing Techniques (IJERT) 2(10) (October 2013) ISSN: 2278-0181

    Google Scholar 

  21. Patwari, M.B., Manza, R.R., Rajput, Y.M., Deshpande, N.K., Saswade, M.: Extraction of the Retinal Blood Vessels and Detection of the Bifurcation Points. IJCA (September 18, 2013) ISBN : 973-93-80877-61-7

    Google Scholar 

  22. Hatanaka, Y.: Automated microaneurysm detection method based on double-ring filter and feature analysis in retinal fundus images. 978-1-4673-2051-1/12 IEEE

    Google Scholar 

  23. SujithKumar, S.B., et al.: Automatic Detection of Diabetic Retinopathy in Non- dilated RGB Retinal Fundus Images. International Journal of Computer Applications 47(19), 888–975 (2012)

    Google Scholar 

  24. Reza, A.W., et al.: Diagnosis of Diabetic Retinopathy: Automatic Extraction of Optic Disc and Exudates from Retinal Images using Marker-controlled Watershed Transformation. J. Med. Syst., doi:10.1007/s10916-009-9426-y

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Patwari Manjiri .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Manjiri, P., Ramesh, M., Yogesh, R., Manoj, S., Neha, D. (2015). Automated Localization of Optic Disk, Detection of Microaneurysms and Extraction of Blood Vessels to Bypass Angiography. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-11933-5_65

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-11933-5_65

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11932-8

  • Online ISBN: 978-3-319-11933-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics