IJSER Home >> Journal >> IJSER
International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 2    
Website: http://www.ijser.org
scirp IJSER >> Volume 1, Issue 2, November-2010
Exudates Detection Methods in Retinal Images Using Image Processing Techniques
Full Text(PDF, 3000)  PP.  
V.Vijayakumari, N. Suriyanarayanan
Capillaries, diabertic retinopathy, exudates ,optc disks
Exudates are one of the most common occurring lesions in diabetic retinopathy. Exudates can be identified as areas with hard white or yellowish colors and varying sizes, shapes and locations near the leaking capillaries within the retina. The detection of exudates is the major goal. For this the pre-requisite stage is the detection of optic disc. Once the optic disc is found certain algorithms could be used to detect the presence of exudates. In this paper few methods are used for the detection and the performance of all the methods are compared.
[1] King H, Aubert RE, Herman WH. “Global burden of diabetesCare 1998; Vol.21: Page 1414- 31.

[2] Sagar A.V., Balasubramaniam S., Chandrasekaran V., “A NovelIntegrated Approach Using Dynamic Thresholding and EdgeDetection (IDTED) for Automatic Detection of Exudates in Digital Fundus Retinal Images” Computing: Theory and Applications, ICCTA’07. International Conference on Issue Date: 5-7March 2007 PP: 705-710 ISBN: 0-7695- INSPEC Accession Number: 9420643 Digital Object Identifier: 10.1109/ICCTA.2007.16

[3] Fong DS, Aiello L, Gardner TW, King GL, Blankenship G, Cavallerano JD, Ferris FL, II, Klein R: Diabetic retinopathy.Diabetes Care 26:226-229, 2003

[4] Huiqili, and Opas Chutatape, (2004) “Automated Feature Extraction in Color Retinal Images by a Model based Approach”,IEEE transactions on biomedical engineering, vol.51, no.2, February 2004 Digital Object Identifier : 10.1109/tbme.2003.820400

[5] Nguyenl, H.T., M. Butler, A. Roychoudhryl, A.G. Shannonl,J. Flack and P. Mitchell, 1996. “Classification of diabeticretinopathy using neural networks”. Proceedings of the 18thAnnual International Conference of the IEEE Engineeringin Medicine and Biology Society, Oct. 31-Nov. 3, Amsterdam,pp: 1548-1549

[6] Kahai, P., K.R. Namuduri and H. Thompson, 2006. A decisionsupport framework for automated screening of diabeticretinopathy. Int. J. Biomed. Imaging., 2006: 1-8.

[7] Milan Sonka,Hlavac and Roger Boyle(2008),Digital ImageProcessing and Computer Vision, Cengage Learning IndiaPrivate Limited.

[8] Wang, H, Wynne Hsu, kheng Guan Goh, Mong Li Lee,(2000). “An Effective Approach to Detect Lesions in ColorRetinal Images”. IEEE Conf. on Computer Vision and PatternRecognition (2000) 181-187, Vol: 2, PP.181-186, ISBN:0-7695-0662-3, INSPEC Accession Number:6651776DOI:10.1109/CVPR.2000.854775

Untitled Page