0d84b514-6e9a-45dc-b79e-5556eaf10fd5 beie director@blueeyesintelligence.org 10.35940/ijitee.A9594.1111121 10.1016/S0161-6420(03)00475-5Wilkinson CP, Ferris III FL, Klein RE, Lee PP, Agardh CD, Davis M, Dills D, Kampik A, Pararajasegaram R, Verdaguer JT, Group GD, "Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales," Ophthalmology, vol. 9, pp. 1677-82, sep 2003.10.1016/j.cmpb.2012.03.009Fraz MM, Remagnino P, Hoppe A, Uyyanonvara B, Rudnicka AR, Owen CG, Barman SA,"Blood vessel segmentation methodologies in retinal images-a survey," Computer methods and programs in biomedicine. Vol. 108, no. 1, pp. 407-33, oct 2012.10.1080/03091900701349602J. Nayak, P. S. Bhat, and U. R. Acharya, "Automatic identification of diabetic maculopathy stage using fundus images," J. Med. Eng. Technol., vol. 33, no. 2, pp. 119-129, Feb. 2009.10.1109/TBME.2010.2096223K. Ram, G. D, Joshi, and J. Sivaswamy, "A successive clutterrejection-based approach for early detection of diabetic retinopathy," IEEE Trans. Biomed. Eng., vol. 58, no. 3, pp. 664-673, Mar. 2011.10.1109/TBME.2012.2205687Fraz MM, Remagnino P, Hoppe A, Uyyanonvara B, Rudnicka AR, Owen CG, Barman SA. An ensemble classification-based approach applied to retinal blood vessel segmentation. IEEE Transactions on Biomedical Engineering, vol. 59 no. 9, pp. 2538-48, jun 2012.10.1007/s10916-007-9113-9J. Nayak, P. S. Bhat, U. R. Acharya, C. M. Lim, and M. Kagathi, "Automated identification of diabetic retinopathy stages using digital fundus images," J. Med. Syst., vol. 32, pp. 107-115, 2008.10.1109/TITB.2008.2007493Osareh, B. Shadgar, and R. Markham, "A computationalintelligence-based approach for detection of exudates in diabetic retinopathy images," IEEE Trans. Inf. Technol. Biomed., vol. 13, no. 4, pp. 535-545, Jul. 2009.10.1007/s00366-011-0253-7M. U. Akram and S. A. Khan, "Multilayered thresholding-based blood vessel segmentation for screening of diabetic retinopathy," Eng. Comput., vol. 29, pp. 165-173, 2013.10.1371/journal.pone.0032435P. Bankhead, C. N. Scholfield, J. G. McGeown, and T. M. Curtis, "Fast retinal vessel setection and measurement using wavelets and edge location refinement," PLOS One, vol. 7, no. 3, pp. 1-12, Mar. 2012.10.1109/TMI.2004.825627J. Staal, M. D. Abramoff, M. Niemeijer, M. A. Viergever, and B. v. Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Trans. Med. Imag., vol. 23, no. 4, pp. 501-509, Apr. 2004.10.1109/TBME.2010.2097599M. S. Miri and A. Mahloojifar, "Retinal image analysis using curvelet transform and multistructure elements morphology by reconstruction," IEEE Trans. Biomed. Eng., vol. 58, no. 5, pp. 1183-1192, May 2011.10.1049/iet-ipr.2012.0134N. G. Ranamuka and R. G. N. Meegama, "Detection of hard exudates from diabetic retinopathy images using fuzzy logic," IET Image Process., vol. 7, no. 2, pp. 121-130, 2013.10.1016/j.patcog.2012.08.009U. T. V. Nguyen, A. Bhuiyan, L. A. F. Park, and K. Ramamohanarao, "An effective retinal blood vessel segmentation method using multiscale line detection," Pattern Recogn., vol. 46, pp. 703-715, 2013.10.1109/JBHI.2013.2294635S. Roychowdhury, D. D. Koozekanani, and K. K. Parhi, "DREAM: Diabetic retinopathy analysis using machine learning," IEEE J. Biomed. Health Inform., vol. 18, no. 5, pp. 1717-1728, Sep. 2014.10.1109/TMI.2015.2409024Y. Zhao, L. Rada, K. Chen, S. P. Harding, and Y. Zheng, "Automated vessel segmentation using infinite perimeter active contour model with hybrid region information with application to retinal images," IEEE Trans. Med. Imag., vol. 34, no.9, pp. 1797-1807, Sep. 2015.10.1155/2015/895267T. Mapayi, S. Viriri, and J-R. Tapamo, "Comparative study of retinal vessel segmentation based on global thresholding techniques," Comput. Math. Method. M., vol. 2015, pp. 1-15, Nov. 2014.10.1016/j.cmpb.2015.01.004E. Imani, M. Javidi, and H-R. Pourreza, "Improvement of retinal blood vessel detection using morphological component analysis," Comput. Meth. Prog. Bio., vol. 118, pp. 263-279, 2015.10.1109/JBHI.2015.2396198A-S. Masoud, H. R. Pourreza, and T. Banaee, "A novel curvature-based algorithm for automatic grading of retinal blood vessel tortuosity," IEEE J. Biomed. Health Inform., vol. 20, no. 2, pp. 586-595, Mar. 2016.10.1109/JBHI.2015.2473159S. Roychowdhury, D. D. Koozekanani, S. N. Kuchinka, and K. K. Parhi, "Optic disc boundary and vessel origin segmentation of fundus images," IEEE J. Biomed. Health Inform., vol. 20, no. 6, pp. 1562- 1574, Nov. 2016.10.1109/TMI.2016.2546227P. Liskowski and K. Krawiec, "Segmenting retinal blood vessels with deep neural networks," IEEE Trans. Med. Imag., vol. 35, no. 11, pp. 2369-2380, Nov. 2016.10.1109/TMI.2015.2509785L. Seoud, T. Hurtut, J. Chelbi, F. Cheriet, and, J. M. P. Langlois, "Red lesion detection using dynamic shape features for diabetic retinopathy screening," IEEE Trans. Med. Imag., vol. 35, no. 4, pp. 1116-1126, Apr. 2016.10.1109/JBHI.2015.2498104R. Pires, S. Avila, H. F. Jelinek, J. Wainer, E. Valle, and A. Rocha, "Beyond lesion-based diabetic retinopathy: a direct approach for retinal," IEEE J. Biomed, Health Inform., vol. 21, no. 1, pp. 193-200, Jan. 2017.10.2337/dc18-0148Verbraak, F.D.; Abramoff, M.D.; Bausch, G.C.F.; Klaver, C.; Nijpels, G.; Schlingemann, R.O.; van der Heijden, A.A. Diagnostic accuracy of a device for the automated detection of diabetic retinopathy in a primary care setting. Diabetes Care,vol. 42, pp. 651-656, 2019.10.1016/j.compeleceng.2018.11.024T. Jebaseeli, Jemima, C. Anand Deva Durai, and J. Dinesh Peter. "Segmentation of retinal blood vessels from ophthalmologic Diabetic Retinopathy images." Computers & Electrical Engineering vol. 73, pp. 245-258, 2019.10.1016/j.artmed.2019.03.009Pires, R.; Avila, S.; Wainer, J.; Valle, E.; Abramoff, M.D.; Rocha, A. A data-driven approach to referable diabetic retinopathy detection. Artif. Intell. Med, vol. 96, pp.93-106, 2019.10.14257/ijgdc.2018.11.1.09S. Dutta, Manideep, B. C., Basha, S. M., Caytiles, R. D., &Iyengar, N. C. S. N. Classification of diabetic retinopathy images by using deep learning models. International Journal of Grid and Distributed Computing, vol. 11, no.1, pp. 89-106, 2019.10.1016/j.compeleceng.2018.11.024T. Jebaseeli, Jemima, C. Anand Deva Durai, and J. Dinesh Peter. "Segmentation of retinal blood vessels from ophthalmologic Diabetic Retinopathy images." Computers & Electrical Engineering, vol. 73, pp. 245-258, 2019.10.1002/mp.13142N. Eladawi, Elmogy, M., Khalifa, F., Ghazal, M., Ghazi, N., Aboelfetouh, A., ...& ElBaz, A,"Early diabetic retinopathy diagnosis based on local retinal blood vessel analysis in optical coherence tomography angiography (OCTA) images," Medical physics, vol. 45, no. 10, pp. 4582-4599, 2018.