Automated detection of diabetic retinopathy from gray-scale fundus images using GLCM and GLRLM-based textural features—a comparative study-Reference-Cited by-同舟云学术

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Automated detection of diabetic retinopathy from gray-scale fundus images using GLCM and GLRLM-based textural features—a comparative study

Published:2025 Issue: Volume: Page:251-259
ISSN:
Container-title:Intelligent Computing Techniques in Biomedical Imaging
language:en
Short-container-title:

Author:

Gupta Subhanshu,Sisodia Dilip Singh

Publisher

Elsevier

Reference26 articles.

1. IDF diabetes atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045;Sun;Diabetes Res. Clin. Pract.,2022

2. Automated identification of diabetic retinopathy stages using digital fundus images;Nayak;J. Med. Syst.,2008

3. Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering;Sisodia,2020

4. Textural features for image classification;Haralick;IEEE Trans. Syst. Man. Cybern., SMC-3,1973

5. Texture information in run-length matrices;Tang;IEEE Trans. Image Process.,1998

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