References
[1]. Bandara, A. M. R. R., & Giragama, P. W. G. R. M. P. B. (2017, December). A retinal image enhancement technique for blood vessel segmentation algorithm. In 2017, IEEE International Conference on Industrial and Information Systems (ICIIS) (pp. 1-5). IEEE. https://doi.org/10. 1109/ICIINFS.2017.8300426
[2]. Kaur, T., Singh, J., Rehani, V., Sharma, A., & John, A. (2017). Diabetic retinopathy detection system (DRDS); A novel GUI based approach for diabetic retinopathy detection. International Journal of Computational Engineering Research (IJCER), 7(11), 19-29.
[3]. Lopes, A. P., Ribeiro, A., & Silva, C. A. (2019, February). Dilated convolutions in retinal blood vessels segmentation. In 2019, IEEE 6th Portuguese Meeting on Bioengineering (ENBENG) (pp. 1-4). IEEE. https://doi.org/10.1109/ENBENG. 2019.8692520
[4]. Mondal, R., Chatterjee, R. K., & Kar, A. (2017, December). Segmentation of retinal blood vessels using adaptive noise island detection. In 2017, Fourth International Conference on Image Information Processing (ICIIP) (pp. 1-5). IEEE. https://doi.org/10.1109/IC IIP.2017.8313673
[5]. Park, K. B., Choi, S. H., & Lee, J. Y. (2020). M-gan: Retinal blood vessel segmentation by balancing losses through stacked deep fully convolutional networks. IEEE Access, 8, 146308-146322. https://doi.org/10.1109/ACCESS.2020.30 15108
[6]. Ratanapakorn, T., Daengphoonphol, A., Eua-Anant, N., Yospaiboon, Y., & Yospaiboon Y. (2019). Digital image processing software for diagnosing diabetic retinopathy from fundus photograph. Clinical Ophthalmology, 13, 641- 648. https://doi.org/10.2147/OPTH.S195617
[7]. Subhashini, R., Nithin, T. N. R., & Koushik, U. M. S. (2019). Diabetic retinopathy detection using image processing (GUI). International Journal of Recent Technology and Engineering, 8(2S3), 538-542. https://doi.org/10.35940/ijr te.B1097.0782S319
[8]. Venkatalakshmi, B., Saravanan, V., & Niveditha, G. J. (2011, May). Graphical user interface for enhanced retinal image analysis for diagnosing diabetic retinopathy. In 2011, IEEE 3rd International Conference on Communication Software and Networks (pp. 610-613). IEEE. https://doi.org/ 10.1109/ICCSN.2011.6014967
[9]. Wankhede, P. R., & Khanchandani, K. B. (2018, December). Retinal Blood Vessel Segmentation in Fundus Images using Improved Graph Cut Method. In 2018, International Conference on Smart Systems and Inventive Technology (ICSSIT) (pp. 555-558). IEEE. https://doi.org/10. 1109/ICSSIT.2018.8748531