Document Type
Conference Item (Restricted)
Publication Date
1-1-2010
Abstract
People with diabetes may face eye problem as a complication of diabetes. These eye problems can cause vision loss and even blindness. There are several lesions that appear such microaneurysms, hemorrhages, cotton wool spots and exudates. Exudates tend to form ring, around area of diseased vessel and appeared as yellowish-white deposits with well-defined edges meanwhile cotton wool spots are grayish-white with poorly defined fluffy edges. Exudates can be highlighted from the background easier rather than cotton wool spots since it has well defined edge. In order to detect these lesions, a proper technique is needed to segment the cotton wool spots and exudates from the background. Therefore, this paper is proposed to sharpen the edge to simplify the segmentation process for cotton wool spots and exudates through ramp width reduction.
Keywords
Diabetic retinopathy, Edge sharpening, Exudates detection, Cotton-wool spots, Diseased vessels, Microaneurysms, Segmentation process, Vision loss, Width reduction, Cotton, Cybernetics, Intelligent systems, Wool, Yarn, Eye protection.
Divisions
fac_eng
Event Title
2010 IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2010
Event Location
Singapore
Event Dates
2010
Event Type
conference
Additional Information
Conference code: 81515 Export Date: 28 January 2013 Source: Scopus Art. No.: 5518585 doi: 10.1109/ICCIS.2010.5518585 Language of Original Document: English Correspondence Address: Yazid, H.; Electrical Engineering Department, University of Malaya, Kuala Lumpur, Malaysia; email: haniza.yazid@gmail.com References: Ooyub, S., Ismail, F., Daud, N.A., (2004) Diabetes Program in Malaysia-Current and Future, NCD Malaysia, 3 (2); Sanchez, C.I., Hornero, R., Lopez, M.I., Poza, J., Retinal image analysis to detec tht and quantify lesions associated with diabetic retinopathy (2004) Proc 26 IEEE Annual International Conf. on Engineering in Medicine and Biology Society (EMBC), 3, pp. 1624-1627; Li, H., Chutatape, O., A model-based approach for automated feature extraction in fundus images (2003) ICCV, pp. 394-399; Walter, T., Klein, J.C., Segmentation of color fundus images of the human retina: Detection of the optic disc and the vascular tree using morphological techniques (2001) Proceedings of the Second International Symposium: Medical Data Analysis, pp. 282-287. , Madrid, Spain October; Wang, H., Hsu, W., Goh, K.G., Lee, M.L., An effective approach to detect lesions in color retinal images (2000) Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 181-186. , Hilton Head Island, USA; Sagar, A.V., Balasubramaniam, S., Chandrasekaran, V., A novel integrated approach using dynamic thresholding and edge detection(IDTED) for automatic detection of exudates in digital fundus images (2007) ICCTA, pp. 705-710; Ege, B.M., Hejlesen, O.K., Ole, V.L., Karina, M., Barry, J., David, K., Cavan, D.A., Screening for diabetic retinopathy using computer based image analysis and statistical classification (2000) Computer Methods and Programs in Biomedicine, 62 (3), pp. 165-175; Lue, J.G., Edge sharpening through ramp width reduction (2000) Image and Vision Computing, 18, pp. 501-514