Loading

Detection of Diabetic Retinopathy
R. B. Kakkeri1, Sayali Surve2, Shahrukh Shaikh3, Vinita Dhoble4

1R. B. Kakkeri, M. Tech, Department of Electronics & Tele Communication Engineering, VLSI Design and Embedded Systems, Asst. Prof at Sinhgad Academy of Engineering, Pune (Maharashtra). India.
2Sayali Surve, B.E. Student, Department of Electronics & Tele Communication Engineering, Sinhgad Academy of Engineering, Pune (Maharashtra). India.
3Shahrukh Shaikh, B.E. Student, Department of Electronics & Tele Communication Engineering, Sinhgad Academy of Engineering, Pune (Maharashtra). India.
4Vinita Dhoble, B.E. Student, Department of Electronics & Tele Communication Engineering, Sinhgad Academy of Engineering, Pune (Maharashtra). India.
Manuscript received on 11 May 2016 | Revised Manuscript received on 22 May 2016 | Manuscript Published on 30 May 2016 | PP: 12-15 | Volume-5 Issue-12, May 2016 | Retrieval Number: L22990551216/2016©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Diabetes is well known disease and may cause abnormalities in the retina (diabetic retinopathy), kidneys (diabetic nephropathy), nervous system (diabetic neuropathy) and is known to be a major risk for cardiovascular diseases. Diabetic retinopathy is a micro vascular complication caused by diabetes, which can lead to blindness. In early stages of diabetic retinopathy typically there are no visible signs, but the number and severity of abnormalities increase during the time. Diabetic retinopathy typically starts with small changes in retinal capillaries. This phenomenon is called neovascularization, which is a serious eyesight threatening state and may cause sudden loss in visual acuity or even permanent blindness. For automated screening programs to work robustly efficient image processing and analysis algorithms have to be developed. This work examines recent literature on digital image processing in the field of early detection of diabetic retinopathy using fundus photographs. Diabetic retinopathy pathologies were further categorized into several groups. In this paper several different databases are presented, and their characteristics discussed.
Keywords: Diabetic Nephropathy, Diabetic Neuropathy Diabetic, work, Automated Screening
Scope of the Article: Network Traffic Characterization and Measurements