[1] [1] MULLINS J.China registers success with TB-diabetes screening initiative［J］. Lancet, 2012, 380(9842): 635-636.

[2] [2] ASKEW D A, CROSSLAND L, WARE R S, et al.. Diabetic retinopathy screening and monitoring of early stage disease in general practice: design and methods ［J］. Contemporary clinical trials, 2012, 33(5): 969-975.

[3] [3] SJOLIE A K, KLEIN R, PORTA M, et al.. Rtinal microaneurysm count predicts progression and regression of diabetic retinopathy［J］. Diabetic Medicine, 2011, 28(3): 345-351.

[4] [4] KANDE G B, SAVITHRI T S, SUBBAIAH P V. Automatic detection of microaneurysms and hemorrhages in digital fundus images［J］. Journal of Digital Imaging, 2010, 23(4): 430-437.

[5] [5] WALTER T, MASSIN P, ERGINAY A, et al.. Automatic detection of microaneurysms in color fundus images ［J］. Medical Image Analysis, 2007, 11(6): 555-566.

[6] [6] AKRAM M U, KHALID S, KHAN S A. Identification and classification of microaneurysms for early detection of diabetic retinopathy ［J］. Pattern Recognition, 2013, 46(1): 107-116.

[7] [7] JIMENEZ S, ALEMANY P, NUNEZ F J, et al.. Automated detection of microaneurysms by using region growing and fuzzy artmap neural network［J］. Archivos de la Sociedad Espanola de Oftalmologia, 2012, 87(9): 284-289.

[8] [8] SHAEIDI A. An algorithm for identification of retinal microaneurysms［J］. Journal of the Serbian Society for Computational Mechanics, 2010, 4(1): 43-51.

[9] [9] ZHANG B, KARRAY F, LI Q, et al.. Sparse representation classifier for microaneurysm detection and retinal blood vessel extraction ［J］. Information Sciences, 2012, 200: 78-90.

[10] [10] ANTAL B, HAJDU A. An ensemble-based system for microaneurysm detection and diabetic retinopathy grading ［J］. IEEE Transactions on Biomedical Engineering, 2012, 59(6): 1720-1726.

[11] [11] AKRAM M U, KHAN A, IQBAL K, et al.. Retinal images: optic disk localization and detection ［C］. International Conference on Image Analysis and Recognition, 2010, 6112: 40-49.

[12] [12] YAZID H, AROF H, ISA H M. Exudates segmentation using inverse surface adaptive thresholding ［J］. Measurement, 2012, 45(6): 1599-1608.

[13] [13] NIEMEIJER M, GINNEKEN B V, CREE M, et al.. Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs ［J］. IEEE Transactions on Medical Imaging, 2010, 1(29): 185-195.

[14] [14] FLEMING A D, PHILIP S, GOATMAN K A, et al.. Automated microaneurysms detection using local contrast normalization and local vessel detection［J］. IEEE Transactions on Medical Imaging, 2006, 25(9): 1223-1232.

[15] [15] QUELLEC G, LAMARD M, JOSSELIN P M, et al.. Optimal wavelet transform for the detection of microaneurysms in retina photographs［J］. IEEE Transactions on Medical Imaging, 2008, 27(9): 1230-1241.

[16] [16] RAM K, JOSHI G D, SIVASWAMY J．A successive clutter-rejection-based approach for early detection of diabetic retinopathy ［J］. IEEE Transactions on Biomedical Engineering, 2011, 58(3): 664-673.

[17] [17] QUELLEC G, RUSSELL S R, MICHAEL D, et al.. Optimal filter framework for automated, instantaneous detection of lesions in retinal images［J］. IEEE Transactions on Biomedical Engineering, 2011, 30(2): 523-533.