Diagnosis of diabetic retinopathy by employing image processing technique to detect exudates in retinal images

Author:

Franklin Sundararaj Wilfred1,Rajan Samuelnadar Edward2

Affiliation:

1. Department of Electronics and Communication EngineeringCSI Institute of TechnologyThovalai, Kanyakumari DistrictNagercoil629302TamilnaduIndia

2. Department of Electrical and Electronics EngineeringMepco Schlenk Engineering CollegeSivakasi626005TamilnaduIndia

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Cited by 39 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. Automatic detection of microaneurysms using DeTraC deep convolutional neural network classifier with woodpecker mating algorithm;The Imaging Science Journal;2024-06-26

2. Wide-field fundus camera using smartphone’s macro-camera for Diabetic Retinopathy screening;Optica Pura y Aplicada;2024-03-31

3. Efficient diabetic retinopathy diagnosis through U-Net – KNN integration in retinal fundus images;Automatika;2023-08-30

4. Exudate Detection in Fundus Images Using Deep Learning Algorithms;Handbook of Research on Thrust Technologies’ Effect on Image Processing;2023-06-30

5. Fundus Image Classification: A Wavelet Feature Descriptor Approach;2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC);2022-11-19

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