[2] SUN Y K. Medical image processing techniques based on optical coherence tomography and their applications ［J］.Opt. Precision Eng., 2014, 22(4): 1086-1104.(in Chinese)
[3] CHAUDHURI S, CHATTERJEE S, KATZ N. Detection of blood vessels in retinal images using two-dimensional matched filters ［J］.IEEE Transactions on Medical Imaging, 1989, 8(3): 263-269.
[4] HOOVER A D, KOUZNETSOVA V, GOLDBAUM M. Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response ［J］.IEEE Transactions on Medical Imaging, 2000, 19(3): 203-210.
[5] MMENDONCA A M, CAMPILHO A. Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction ［J］.IEEE Transactions on Medical Imaging, 2006, 25(9): 1200-1213.
[6] RICCI E, PERFETTI R. Retinal blood vessel segmentation using line operators and support vector classification ［J］.IEEE Transactions on Medical Imaging, 2007, 26(10): 1357-1365.
[7] STAAL J, ABRMOFF M D, NIEMEIJER M. Ridge-based vessel segmentation in color images of the retina ［J］.IEEE Transactions on Medical Imaging, 2004, 23(4): 501-509.
[8] SOARES J V B, LEANDRO J J G, CESAR R M. Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification ［J］.IEEE Transactions on Medical Imaging, 2006, 25(9): 1214-1222.
[9] MARN D, AQUINO A, GEGUC＇NDEZ-ARIAS M E, et al.. A new supervised method for blood vessel segmentation in retinal images by using gray-level and moment invariants-based features ［J］.IEEE Transactions on Medical Imaging, 2011, 30(1): 146-158.
[10] FRAZ M M, REMAGNINO P, HOPPE A, et al..An ensemble classification-based approach applied to retinal blood vessel segmentation ［J］.IEEE Transactions on Biomedical Engineering, 2012, 59(9): 2538-2548.
[11] AZZOPARDI G, PETKOV N. A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model ［J］.Biological Cybernetics, 2012, 106(3): 177-189.
[12] AZZOPARDI G, STRISCIUGLIO N, VENTO M. Trainable COSFIRE filters for vessel delineation with application to retinal images ［J］.Medical Image Analysis, 2015, 19(1): 46-57.
[13] LUPASCU C A, TEGOLO D, TRUCCO E. FABC: retinal vessel segmentation using AdaBoost［J］.IEEE Transactions on Information Technology in Biomedicine, 2010, 14(5): 1267-1274.
[14] SHAHRIAN E V, YOUSEFI S, ISFAHANI A M. Vessels segmentation in color retinal images using ensemble of bagged decision trees and patched based principle component analysis and linear discriminant analysis ［J］.Investigative Ophthalmology & Visual Science, 2015, 56(7): 5262.
[15] ZHU C Z, ZOU B J, ZHAO R C. Retinal vessel segmentation in colour fundus images using Extreme Learning Machine ［J］.Computerized Medical Imaging and Graphics, 2017, 55(SI): 68-77.
[16] HATANAKA Y, TACHIKI H, OGOHARA K. Artery and vein diameter ratio measurement based on improvement of arteries and veins segmentation on retinal images ［C］. 2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC), IEEE, 2016: 1336-1339.
[17] RODRIGUES J, BEZERRA N. Retinal vessel segmentation using parallel grayscale skeletonization algorithm and mathematical morphology［C］.Conference on Graphics, Patterns and Images, 2016.
[18] OLIVEIRA W S, TEIXEIRA J V, REN T I. Unsupervised retinal vessel segmentation using combined filters ［J］.PloS one, 2016, 11(2): e0149943.
[19] LU C Y, JING B Z, CHAN P P K. Vessel enhancement of low quality fundus image using mathematical morphology and combination of Gabor and matched filter ［C］. 2016 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), IEEE, 2016: 168-173.
