Automated Drusen Detection Technique for Age-Related Macular Degeneration


  • Kajal Kumari "Thapar University"
  • Deepti Mittal "Thapar University"



age-related macular degeneration, region based statistical analysis, area based statistics, correction of background illumination, drusen, morphological operation, Otsu's threshold


Age-related macular degeneration is one of the leading cause of vision loss and blindness among people of age 50 and higher. Macular degeneration is usually characterized by drusen. Drusens are accumulation of lipids, fatty proteins that appears as abnormal white-yellow deposits on the retina. Detection of these lesions using conventional image analysis methods is quite complicated and time taking mainly due to non-uniform illumination and the variability of the pigmentation of the background tissues. This paper presents an automated technique for segmentation and quantitative analysis of drusen in publicly available retinal images i.e. Structured Analysis of retina (STARE) and Automated Retinal Image Analysis (ARIA), acquired with the aid of a digital fundus camera. The present methodology emphasizes on quantitative analysis of drusen based on: First, region-based statistical analysis which corrects the non-uniform illumination of background, enhances local intensity, minimizes image noise, segment image through Otsu’s threshold in addition with morphological operation and hence compute area and edge of the detected drusen. Second, pixel-wise feature extraction which extracts the feature of overlapped components through weighted centroid and standard deviation, makes counting of number of drusen easy. Hence, this system can provide vital information about the quantity of drusen and can aid clinicians in their diagnosis to evaluate the stage of age-related macular degeneration. 

Author Biographies

Kajal Kumari, "Thapar University"

Electrical and Instrumentation Department, M.E student

Deepti Mittal, "Thapar University"

department of Electrical and Instrumentation Engineering, Assistant Professor


Resnikoff, Pascolini, et al. Global data on visual impairment in the year 2002. Bulletin of the World Health Organization, vol. 82, 2004. p: 844-851.

De Jong, Age-related macular degeneration. The New England Journal of Medicine, 355(14), 2006. p: 1474-1485.

Age-related Eye Disease Study Research Group, The age-related eye disease study system for classifying age-related macular degeneration from stereoscopic color fundus photographs: the age-related eye disease study report number 6. American Journal of Ophthalmology, vol. 132, 2001. p: 668-681.

Smith, Chan, et al. A method of drusen measurement based on reconstruction of fundus background reflectance. Br J Ophthalmol, 2005. 89: p: 87-91.

Rapantzikos, M. Zervakis, et al. Detection and segmentation of drusen deposits on human retina: Potential in the diagnosis of age-related macular degeneration. Medical image Analysis 7, 2003. p: 95-108.

Thaibaoui, Raji, et al. A Fuzzy Approach to Drusen Detection in Retinal Angiographic Images. IEEE, 2000. p: 748-751.

Checco, Corinto, Cnn-based algorithm for drusen identification. 2006 IEEE International Symposium on Circuits and Systems, 2006. p: 2181-2184.

Mora et al. Automated drusen detection in retinal images using analytical modelling algorithms. Biomedical Engineering Online, 2011. p: 10:59.

Lee, Smith, et al. Learning Non-Homogenous Textures and the Unlearning Problems with Application to Drusen Detection in Retinal Images. IEEE, 2008. p: 1215-1218.

Zheng, Vanderbeek, et al. An Automated Drusen Detection System for Classifying Age-Related Macular Degeneration with Color Fundus Photographs. IEEE 10th International Symposium on Biomedical Imaging, 2013. p: 1448-1451.

Raza, Rafique, et al. Hybrid Classifier Based Drusen Detection in Colored Fundus Images. IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, 2013. p: 8-13.

Rama Prasath, M.M.Ramaya, Automatic Detection and Elimination of an Optic Disc for Improving Drusen Detection Accuracy. Fifth International Conference on Signal and Image Processing, 2014. p: 117-121.

Gonzalez, R. and R. Gonzalez, R. and R. Woods (2007). Digital Image Processing – third addition, Prentice-Wall.

Gupta, Purkayashta, Statistical Particle Analysis in Microscopic Images using Morphology. International Journal of Science and Advance Technology, 2012. Vol. 1, No. 1, p: 35-40.

N Otsu, A threshold selection method from gray-level histogram, IEEE transection on systems, Man and Cybernetics, SMC-8, 1978, p: 62-66.

ARIA database from

STARE database from

D. Jayanthi, Devi, et al. Automatic diagnosis of retinal diseases from color retinal images. International journal of computer science and Information Security, 2010. Vol. 7, No. 1




How to Cite

Kumari, K., & Mittal, D. (2015). Automated Drusen Detection Technique for Age-Related Macular Degeneration. British Journal of Healthcare and Medical Research, 2(1), 18.

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