Automatic diabetic retinopathy diagnosis using adjustable ophthalmoscope and multi-scale line operator |
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| Affiliation: | 1. University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China;2. Department of Electrical and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;3. Department of Software Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;4. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;5. Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong;6. Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China;1. College of Information and Control Engineering, China University of Petroleum, Qingdao, PR China;2. School of Computer, Wuhan University, Wuhan, PR China;3. School of Information Science and Engineering, Qufu Normal University, Rizhao, PR China;4. College of Computer and Communication Engineering, China University of Petroleum, Qingdao, PR China;1. School of Cyber Engineering, Xidian University, Xi’an, 710071, PR China;2. Department of ECE, Michigan State University, East Lansing, MI, 48824, USA;1. National Engineering Research Center for Communication and Network Technology, Nanjing University of Posts and Telecommunications, China;2. Department of Computing, The Hong Kong Polytechnic University, China;3. The Hong Kong Polytechnic University Shenzhen Research Institute, China;4. College of Engineering, Shantou University, China;1. School of Computer Science and Technology/Suzhou Institute for Advanced Study, University of Science and Technology of China, Hefei, PR China;2. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, PR China;1. ICAR-CNR, Italy;2. DIMES, UNICAL, Italy;1. WINCORE Laboratory in the Department of Electrical and Computer Engineering, Ryerson University, Ontario, Canada;2. COMSATS Institute of Information Technology, Wah Campus, Wah Cantt, Pakistan |
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| Abstract: | Diabetic Retinopathy (DR), the most common one of diabetic eye diseases that cause loss of vision and blindness, has become one of major health problems today. However, DR can be eased through timely treatment and periodical screening. In this paper, we proposes an automatic diabetic retinopathy diagnostic system to help patients know about their retinal conditions. We design a portable ophthalmoscope, which is composed of a retinal lens, a smartphone and a frame between them to help patients take fundus images anywhere and anytime. Then the images are transmitted to be analyzed, including localization of optic disk and macular, vessel segmentation, detection of lesions, and grading of DR. We use a multi-scale line operator to improve accuracy in segmenting small-scale vessels, a binary mask and image restoration to reduce the effect of the existence of the vessels on optic disk localization. After the analysis, the fundus image are then graded as normal, mild Non-Proliferative Diabetic Retinopathy (NPDR), moderate NPDR or severe NPDR. The grading process uses region segmentation to improve the efficiency. The final grading results are tested based on the fundus images provided by the hospitals. We evaluate our system through comparing our grading result with those graded by experts, which comes out with an overall accuracy of up to 85%. |
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| Keywords: | Diabetic retinopathy screening Ophthalmoscope DR grading Multi-scale line operator |
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