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Journal of Computer Science and Technology ›› 2019, Vol. 34 ›› Issue (6): 1307-1318.doi: 10.1007/s11390-019-1977-x
Special Issue: Artificial Intelligence and Pattern Recognition; Computer Graphics and Multimedia
• Computer Graphics and Multimedia • Previous Articles Next Articles
Cheng-Zhang Zhu1,2, Member, CCF, IEEE, Rong Hu2,3, Bei-Ji Zou2,3, Member, CCF, Rong-Chang Zhao2,3, Member, CCF, ACM, Chang-Long Chen2,3, Ya-Long Xiao1,2,*, Member, CCF
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Diagnosis of diabetic retinopathy based on holistic texture and local retinal features. Information Sciences, 2019, 475:44-66. [20] Fleming A D, Philip S, Goatman K A, Williams G J, Olson J A, Sharp P F. Automated detection of exudates for diabetic retinopathy screening. Physics in Medicine and Biology, 2007, 52(24):7385-7396. [21] Yao L, Zeng F, Li D H, Chen Z G. Sparse support vector machine with L p penalty for feature selection. Journal of Computer Science and Technology, 2017, 32(1):68-77. [22] Carrera E V, González A, Carrera R. Automated detection of diabetic retinopathy using SVM. In Proc. the IEEE XXIV International Conference on Electronics, Electrical Engineering and Computing, August 2017, Article No. 58. [23] Canny J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(6):679-698. [24] Raman V, Then P, Sumari P. Proposed retinal abnormality detection and classification approach:Computer aided detection for diabetic retinopathy by machine learning approaches. In Proc. the 8th IEEE International Conference on Communication Software and Networks, June 2016, pp.636-641. [25] Decenciere E, Zhang X, Cazuguel G, Lay B, Cochener B, Trone C, Gain P, Ordonez R, Massin P, Erginay A, Charton B, Klein, J. Feedback on a publicly distributed image database:The Messidor database. Image Analysis and Stereology, 2014, 33(3):231-234. [26] Agurto C, Murray V, Barriga E, Murillo S, Pattichis M, Davis H, Russell S, Abràmoff M, Soliz P. Multiscale AM-FM methods for diabetic retinopathy lesion detection. IEEE Transactions on Medical Imaging, 2010, 29(2):502-512. [27] Quellec G, Lamard M, Abràmoff M D, Decencière E, Lay B, Erginay A, Cochener B, Cazuguel G. A multiple-instance learning framework for diabetic retinopathy screening. Medical Image Analysis, 2012, 16(6):1228-1240. 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Automated early detection of diabetic retinopathy. Ophthalmology, 2010, 117(6):1147-1154. |
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