A Review on Automatic Glaucoma Detection in Retinal Fundus Images

Author:

Shahistha ,Vaidehi K.,Srilatha J.

Publisher

Springer Singapore

Reference20 articles.

1. Del Rincón, A.G.J.M., Miller, P., Azuara Blanco, A.: Automatic analysis of digital retinal images for glaucoma detection

2. Acharya, U., Rajendra, et al.: Decision support system for the glaucoma using Gabor transformation. Biomed. Signal Process. Control 15 (2015)

3. Agarwal, A., et al.: A novel approach to detect glaucoma in retinal fundus images using cup-disk and rim-disk ratio. Bioinspired Intelligence (IWOBI), 2015 4th International Work Conference on. IEEE, 2015

4. Dey, A., Bandyopadhyay. S.K.: Automated glaucoma detection using support vector machine classification method. Br. J. Med. Med. Res. 11(12) (2016)

5. Maheshwari, S., Pachori, R.B., Rajendra Acharya, U.: Automated diagnosis of glaucoma using empirical wavelet transform and correntropy features extracted from fundus images. IEEE J. Biomed. Health Inf.

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1. TWEEC : Computer‐aided glaucoma diagnosis from retinal images using deep learning techniques;International Journal of Imaging Systems and Technology;2021-07-04

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