Detection of Hemorrhages and Microaneurysms Using Image Processing : A Review

Authors(2) :-Bhushan Thakare, Prof. Jayant Adhikari

Here we address the study on detection of Hemorrhages and microaneurysms in color fundus images. In pre-Processing we find different separate red, green, blue color channel from the retinal images. The green channel will pass to the further process. The green color plane was used in the analysis since it shows the best contrast between the vessels and the background retina. Then we extract the GLCM(Gray Level Co-Occurance Matrix) feature. We made a survey of different author who have done their work in this field. We also compare the different data mining techniques that are required to perform detection in proper way.

Authors and Affiliations

Bhushan Thakare
Department of Computer Science and Engineering, TGPCET, Nagpur, Maharashtra, India
Prof. Jayant Adhikari
Department of Computer Science and Engineering, TGPCET, Nagpur, Maharashtra, India

GLCM, Fundus, Hemorrhages, Microaneurysms

  1. S Wild, G. Roglic, A Green et aI., "Global prevalence of diabetes: estimates for the year 2000 and projections for 2030", Diabetes Care, 27, pp.l047-1053, 2004.
  2. National Eye Institute, National Institutes of Health, "Diabetic Retinopathy: What you should know", Booklet, NIH Publication, No: 06-2171,2003.
  3. Fleming, AD., Goatman, KA, et aI., JA & Scottish Diabetic Retinopathy Clinical Research Network (2010), "The role of haemorrhage and exudate detection in automated grading of diabetic retinopathy", British Journal of Ophthalmology, vol 94, no. 6, pp. 706- 711.
  4. Dupas B, Walter T, Erginay A, et aI., "Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy", Diabetes Metab, Jun;36(3), pp.213-20., Epub 2010.
  5. GB. Kande, S.S. Tirumala, P.V. Subbaiah, and M.R. Tagore, "Detection of Red Lesions in Digital Fundus Images", in Proc. ISBI, pp.558-561,2009.
  6. CMarino, E. Ares , M.G.Penedo, M. Ortega, N. Barreira, F. GomezU1Ia, "Automated Three Stage Red Lesions Detection In Digital Color Fundus Images", WSEAS Transactions on Computers, vol. 7, pp. 207- 215,2008.
  7. M Esmaeili, H. Rabbani, AM. Dehnavi, and A Dehghani, "A new curvelet transform based method for extraction of red lesions in digital color retinal images", in Proc. ICIP" pp.4093-4096, 2010.
  8. Garcia M, Lopez MI, Alvarez D, Hornero R., "Assessment of four neural network based classifiers to automatically detect red lesions in retinal images", Med Eng Phys. 2010 Dec;32(1O):1085-93. Epub 2010.
  9. Niemeijer M, van Ginneken B, Staal J, Suttorp-SchuItenMSA, Abrmoff MD., "Automatic detection of red lesions in digital color fundus photograph". IEEE Trans Med lmag 24(5):584592, 2005

Publication Details

Published in : Volume 4 | Issue 6 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 195-198
Manuscript Number : IJSRSET1848150
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Bhushan Thakare, Prof. Jayant Adhikari, " Detection of Hemorrhages and Microaneurysms Using Image Processing : A Review, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 6, pp.195-198, January-February.2018
URL : http://ijsrset.com/IJSRSET1848150

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