[1] Baker M L, Hand P J, Wang J J et al. Retinal signs and stroke[J]. Stroke, 39, 1371-1379(2008).

[2] Patton N, Aslam T. MacGillivray T, et al. Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures[J]. Journal of Anatomy, 206, 319-348(2005).

[3] Wang X H, Xue Q S. Optical design of portable non-mydriatic fundus camera with large field of view[J]. Acta Optica Sinica, 37, 0922001(2017).

[4] Chaudhuri S, Chatterjee S, Katz N et al. Detection of blood vessels in retinal images using two-dimensional matched filters[J]. IEEE Transactions on Medical Imaging, 8, 263-269(1989).

[5] Yang Y, Huang S Y, Rao N N. An automatic hybrid method for retinal blood vessel extraction[J]. International Journal of Applied Mathematics and Computer Science, 18, 399-407(2008).

[6] Li Q, You J, Zhang D. Vessel segmentation and width estimation in retinal images using multiscale production of matched filter responses[J]. Expert Systems With Applications, 39, 7600-7610(2012).

[7] Zhao Y T, Rada L, Chen K et al. Automated vessel segmentation using infinite perimeter active contour model with hybrid region information with application to retinal images[J]. IEEE Transactions on Medical Imaging, 34, 1797-1807(2015).

[8] Staal J, Abramoff M D, Niemeijer M et al. Ridge-based vessel segmentation in color images of the retina[J]. IEEE Transactions on Medical Imaging, 23, 501-509(2004).

[9] Soares J V B, Leandro J J G, Cesar R M et al. Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification[J]. IEEE Transactions on Medical Imaging, 25, 1214-1222(2006).

[10] Ricci E, Perfetti R. Retinal blood vessel segmentation using line operators and support vector classification[J]. IEEE Transactions on Medical Imaging, 26, 1357-1365(2007).

[11] 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, 59, 2538-2548(2012).

[12] Shelhamer E, Long J, Darrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 640-651(2017).

[13] Wang S L, Yin Y L, Cao G B et al. Hierarchical retinal blood vessel segmentation based on feature and ensemble learning[J]. Neurocomputing, 149, 708-717(2015).

[14] Ronneberger O, Fischer P, Brox T[M]. U-net: convolutional networks for biomedical image segmentation, 234-241(2015).

[15] Alom M Z, Hasan M, Yakopcic C, for medical image segmentation[EB/OL] et al. -02-19)[2020-01-18]. http: ∥arxiv., org/abs/1802, 06955(2018).

[16] He K, Zhang X, Ren S et al. -11-10)[2020-01-18]. https: ∥arxiv., org/abs/1512, 03385(2015).

[17] Ioffe S, Szegedy C. Batch normalization: accelerating deep network training by reducing internal covariate shift. [C]∥32 ^nd International Conference on International Conference on Machine Learning, July 6-11, 2015, Lille, France. [S.l. : s.n. ], 37, 448-456(2015).

[18] Oktay O, Schlemper J, Folgoc L L et al. -05-20) [2020-01-18]. http: ∥arxiv., org/abs/1804, 03999(2018).

[19] Noh H, Hong S, Han B. Learning deconvolution network for semantic segmentation. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015. Santiago, Chile. New York: IEEE, 1520-1528(2015).

[20] Zheng T Y, Tang C, Lei Z K. Multi-scale retinal vessel segmentation based on fully convolutional neural network[J]. Acta Optica Sinica, 39, 0211002(2019).

[21] 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, 19, 203-210(2000).

[22] Kingma D P. -01-30)[2020-01-18]. https: ∥arxiv., org/abs/1412, 6980(2017).

[23] Lam B S Y, Gao Y S, Liew W C. General retinal vessel segmentation using regularization-based multiconcavity modeling[J]. IEEE Transactions on Medical Imaging, 29, 1369-1381(2010).

[24] Fraz M M, Remagnino P, Hoppe A et al. Blood vessel segmentation methodologies in retinal images: A survey[J]. Computer Methods and Programs in Biomedicine, 108, 407-433(2012).

[25] You X G, Peng Q M. Yuan, et al. Segmentation of retinal blood vessels using the radial projection and semi-supervised approach[J]. Pattern Recognition, 44, 2314-2324(2011).

[26] Azzopardi G, Strisciuglio N, Vento M et al. Trainable COSFIRE filters for vessel delineation with application to retinal images[J]. Medical Image Analysis, 19, 46-57(2015).

[27] Marín D, Aquino A. Gegundez-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, 30, 146-158(2011).

[28] Roychowdhury S, Koozekanani D D, Parhi K K. Blood vessel segmentation of fundus images by major vessel extraction and sub-image classification[J]. IEEE Journal of Biomedical and Health Informatics, 19, 1118-1128(2014).

[29] Liskowski P, Krawiec K. Segmenting retinal blood vessels with deep neural networks[J]. IEEE Transactions on Medical Imaging, 35, 2369-2380(2016).

[30] Li Q L, Feng B W, Xie L P et al. A cross-modality learning approach for vessel segmentation in retinal images[J]. IEEE Transactions on Medical Imaging, 35, 109-118(2016).