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Automated detection of exudates in colored retinal images for diagnosis of diabetic retinopathy

  • Published:2012-07-09 Issue:20 Volume:51 Page:4858
  • ISSN:1559-128X
  • Container-title:Applied Optics
  • language:en
  • Short-container-title:Appl. Opt.

Author:

Akram M. Usman,Tariq Anam,Anjum M. Almas,Javed M. Younus

Publisher

The Optical Society

Subject

Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering

Cited by 37 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An attention enriched encoder–decoder architecture with CLSTM and RES unit for segmenting exudate in retinal images;Signal, Image and Video Processing;2024-02-10

2. DTUNet: dual branch transformer U-Net for hard exudate segmentation in retinal image;Journal of Electronic Imaging;2023-08-01

3. Diabetic Retinopathy Detection Using Optimized Random Under Sampling (ORUS) Algorithm;International Journal of Scientific Research in Science and Technology;2023-04-01

4. Channel Attention Enhanced Deep Network for Segmenting Exudate;2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON);2022-12-17

5. Spatial Attention Enhanced Network for Segmentation of Exudate;2022 IEEE Calcutta Conference (CALCON);2022-12-10
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