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An Automated Approach to Differentiate a Normal eye from a Defective Eye

by Hillol Das, Ashim Saha, Suman Deb, Gautam Nath
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 79 - Number 15
Year of Publication: 2013
Authors: Hillol Das, Ashim Saha, Suman Deb, Gautam Nath
10.5120/13816-1810

Hillol Das, Ashim Saha, Suman Deb, Gautam Nath . An Automated Approach to Differentiate a Normal eye from a Defective Eye. International Journal of Computer Applications. 79, 15 ( October 2013), 10-15. DOI=10.5120/13816-1810

@article{ 10.5120/13816-1810,
author = { Hillol Das, Ashim Saha, Suman Deb, Gautam Nath },
title = { An Automated Approach to Differentiate a Normal eye from a Defective Eye },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 79 },
number = { 15 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 10-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume79/number15/13816-1810/ },
doi = { 10.5120/13816-1810 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:53:03.955142+05:30
%A Hillol Das
%A Ashim Saha
%A Suman Deb
%A Gautam Nath
%T An Automated Approach to Differentiate a Normal eye from a Defective Eye
%J International Journal of Computer Applications
%@ 0975-8887
%V 79
%N 15
%P 10-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Detection of basic differentiating characteristics of eye diseases from the images of the retina can be a good approach as a low-cost method for broad-based initial screening. For example early diabetic retinopathy detection enables application of laser therapy treatment in order to prevent or delay loss of vision. The paper has referenced Diabetic retinopathy and Retinitis pigmentosa for analysis. Automated approach for detection of microaneurysms in digital color fundus photographs helps ophthalmologist to detect the emergence of its initial symptoms and determine the next action step for the patient. A similar mechanism for automated early disease detection method with respect to the features of the normal eye is proposed. The detection algorithm features identification of black pigments like minute features, microaneurysm and exudate detection and these features extracted can prove to a greater extent as ready instances for defectiveness. A number of images along with the feedback and consultation from the ophthalmologist in this area of medical science has proved to be a great help towards the observation as derived from this mechanism and discussed in the later end of this paper. The proposed mechanism can be extended up to the limit of supervised learning so as to automate the practical feedbacks as obtained from the practitioners.

References
  1. R. Vidyasari, I. Sovani, and T. L. R. Mengko, H. Zakaria, "Vessel Enhancement Algorithm in Digital Retinal Fundus Microaneurysms Filter for Nonproliferative Diabetic Retinopathy Classification", 2011 International Conference on Instrumentation, Communication, Information Technology and Biomedical Engineering 8-9 November 2011, Bandung, Indonesia.
  2. Langston, DB. (1988). "Manual of Ocular Diagnosis and Therapy", Little Brown Company, Boston.
  3. M. U. Akram, I. Jamal, A. Tariq, J. Imtiaz, "Automated segmentation of blood vessels for detection of proliferative diabetic retinopathy", Biomedical and Health Informatics (BHI), IEEE-EMBS International Conference on, vol. , no. , pp. 232-235, 5-7, 2012.
  4. D. Vallabha, R. Dorairaj, K. Namuduri, H. Thompson, "Automated detection and classification of vascular abnormalities in diabetic retinopathy", Signals, Systems and Computers, Conference Record of the Thirty-Eighth Asilomar Conference on, vol. 2, pp. 1625-1629 Vol. 2, Nov. 2004.
  5. M. A. Bamashmus, B. Matlhaga and G. N. Dutton, "Causes of blindness and visual impairment in the west of scotland", Eye, vol. 18, pp. 257–261, 2004.
  6. Giancardo, L. , Abramoff, M. D. , Chaum, E. , Karnowski, T. P. , Meriaudeau, F. , and Tobin, K. W. , (2008), "Elliptical local vessel density: a fast and robust quality metric for fundus images", 30th Annual International Conf. of the IEEE EMBS Vancouver, Canada, 2008.
  7. Giancardo, L. , et. al, (2010), "Microaneurysms detection with the Radon Cliff operator in retinal fundus images", Proc. SPIE Medical Imaging, San Diego CA, 7623:7623.
  8. Giancardo, L. , et. al, (2011), "Automatic retina exudates segmentation without a manually labeled training set", Proc. IEEE International Symposium on Biomedical Imaging.
  9. Tobin KW, Chaum E, Govindasamy VP, Karnowski TP. (2007), "Detection of anatomic structures in human retinal imagery", IEEE Trans Med Imaging 26:1729-39.
  10. Chaum, E. , Karnowski, T. P. , Govindasamy, V. P. , Abdelrahamen M, Tobin K. W. , (2008), "Automated diagnosis of retinopathy by content based image retrieval", Retina 28:1463-1477.
  11. http://www5. cs. fau. de/research/data/fundus-images/
  12. Agung W. Setiawan, Tati R. Mengko, Oerip S. Santoso and Andriyan B. Suksmono, "Color Retinal Image Enhancement using CLAHE", 2013 International Conference on ICT for Smart Society (ICISS).
  13. http://www2. it. lut. fi/project/imageret/diaretdb0/index. htm
Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Retinitis Pigmentosa microaneurysms opthalmologist.