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Scientifica
Volume 2016, Article ID 6838976, 20 pages
http://dx.doi.org/10.1155/2016/6838976
Review Article

A Review on Recent Developments for Detection of Diabetic Retinopathy

COMSATS Institute of Information Technology, Department of Computer Science, Wah 47040, Pakistan

Received 14 December 2015; Revised 22 April 2016; Accepted 10 May 2016

Academic Editor: Gary Lopaschuk

Copyright © 2016 Javeria Amin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [11 citations]

The following is the list of published articles that have cited the current article.

  • Ustundag Yasemin, Akdogan Müberra, Barazi Ayse, Cevik Sadik Gorkem, Demirci Hakan, Günay Leyla, and Huysal Kagan, “High density lipoprotein-3 in diabetic retinopathy patients: relationship to total antioxidant capacity and nitric oxide level,” International Eye Science, vol. 17, no. 12, pp. 2197–2202, 2017. View at Publisher · View at Google Scholar
  • Ying Yin, Yu Xin, Jian Zou, Yong Yao, Jun Shao, Xiaowen Yin, and Li Ji, “Transthyretin Exerts Pro-Apoptotic Effects in Human Retinal Microvascular Endothelial Cells Through a GRP78-Dependent Pathway in Diabetic Retinopathy,” Cellular Physiology and Biochemistry, vol. 43, no. 2, pp. 788–800, 2017. View at Publisher · View at Google Scholar
  • V. Ganesh Babu, Saraswathi, Reka, and Parithimarkalaignan, “RPC Approach to know the level of microaneurysms in mild juncture of nonproliferative diabetic retinopathy,” International Journal of Pure and Applied Mathematics, vol. 117, no. 9, pp. 125–128, 2017. View at Publisher · View at Google Scholar
  • Ravindra Badgujar, and Pramod Deore, “MBO-SVM-based exudate classification in fundus retinal images of diabetic patients,” Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, pp. 1–12, 2018. View at Publisher · View at Google Scholar
  • R. Suma, Deepashree Devaraj, and S. C. Prasanna Kumar, “Detection of Exudates Through Local Binary Pattern in Diabetic Retinopathy,” Cognitive Computing and Information Processing, vol. 801, pp. 29–39, 2018. View at Publisher · View at Google Scholar
  • Muhammad Sharif, Javeria Amin, Mussarat Yasmin, and Amjad Rehman, “Efficient hybrid approach to segment and classify exudates for DR prediction,” Multimedia Tools and Applications, 2018. View at Publisher · View at Google Scholar
  • Javeria Amin, Muhammad Sharif, Amjad Rehman, Mudassar Raza, and Muhammad Rafiq Mufti, “Diabetic retinopathy detection and classification using hybrid feature set,” Microscopy Research and Technique, vol. 81, no. 9, pp. 990–996, 2018. View at Publisher · View at Google Scholar
  • Tanzila Saba, Syedia Tahseen Fatima Bokhari, Muhammad Sharif, Mussarat Yasmin, and Mudassar Raza, “Fundus image classification methods for the detection of glaucoma: A review,” Microscopy Research and Technique, 2018. View at Publisher · View at Google Scholar
  • Jianxin Tao, Yixin Wang, and Yong Yao, “Prostaglandin e 2 Activates NLRP3 Inflammasome in Endothelial Cells to Promote Diabetic Retinopathy,” Hormone and Metabolic Research, vol. 50, no. 9, pp. 704–710, 2018. View at Publisher · View at Google Scholar
  • Shahzad Akbar, Muhammad Sharif, Muhammad Usman Akram, Tanzila Saba, Toqeer Mahmood, and Mahyar Kolivand, “Automated techniques for blood vessels segmentation through fundus retinal images: A review,” Microscopy Research and Technique, 2019. View at Publisher · View at Google Scholar
  • Uzair Ishtiaq, Sameem Abdul Kareem, Erma Rahayu Mohd Faizal Abdullah, Ghulam Mujtaba, Rashid Jahangir, and Hafiz Yasir Ghafoor, “Diabetic retinopathy detection through artificial intelligent techniques: a review and open issues,” Multimedia Tools and Applications, 2019. View at Publisher · View at Google Scholar