An exudate detection method for diagnosis risk of diabetic macular edema in retinal images using feature-based and supervised classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Biomedical Engineering
Link
http://link.springer.com/article/10.1007/s11517-017-1771-2/fulltext.html
Reference43 articles.
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2. Abràmoff MD, Niemeijer M, Suttorp-Schulten MSA, Viergever MA, Russell SR, van Ginneken B (2008) Evaluation of a system for automatic detection of diabetic retinopathy from color fundus photographs in a large population of patients with diabetes. Diabetes Care 31(2):193–198. https://doi.org/10.2337/dc07-1312
3. Abràmoff MD, Folk JC, Han DP, Walker JD, Williams DF, Russell SR, Massin P, Cochener B, Gain P, Tang L, Lamard M, Moga DC, Quellec G, Niemeijer M (2013) Automated analysis of retinal images for detection of referable diabetic retinopathy. JAMA Ophthalmol 131(3):351–357. https://doi.org/10.1001/jamaophthalmol.2013.1743
4. Ahmad Fadzil MH, Izhar LI, Nugroho H, Nugroho HA (2011) Analysis of retinal fundus images for grading of diabetic retinopathy severity. Med Biol Eng Comput 49(6):693–700. https://doi.org/10.1007/s11517-011-0734-2
5. Alshayeji M, Al-Roomi SA, Abed S (2017) Optic disc detection in retinal fundus images using gravitational law-based edge detection. Med Biol Eng Comput 55(6):935–948. https://doi.org/10.1007/s11517-016-1563-0
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