Deep learning architecture based on segmented fundus image features for classification of diabetic retinopathy

Author:

Das Sraddha,Kharbanda Krity,M Suchetha,Raman Rajiv,D Edwin Dhas

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference39 articles.

1. Optimized maximum principal curvatures based segmentation of blood vessels from retinal images;Santosh;Biomed. Res.,2019

2. Retinal blood vessel segmentation approach based on mathematical morphology;Hassan;Procedia Comput. Sci.,2015

3. A discriminatively trained fully connected conditional random field model for blood vessel segmentation in fundus images;Orlando;IEEE Trans. Biomed. Eng.,2017

4. Analysis of retinal blood vessel segmentation in different types of diabetic retinopathy;Manjula Sri;Int. J. Eng. Adv. Technol. (IJEAT),2019

5. Retinal blood vessel segmentation by using matched filtering and fuzzy C-means clustering with integrated level set method for diabetic retinopathy assessment;Memari;J. Med. Biol. Eng.,2019

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