A hybrid multilayered classification model with VGG-19 net for retinal diseases using optical coherence tomography images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-08928-w.pdf
Reference26 articles.
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2. Dash S, Chowdary PSR, Chakravarthy VVSSS, Raju CG, Sahu G, Charan KS, Umamaheshwar Y (2022) Real time retinal optic disc segmentation via guided filter and discrete wavelet transform. J Phys Conf Ser 2312(1):012007
3. Hassan B, Qin S, Hassan T, Ahmed R, Werghi N (2021) Joint segmentation and quantification of chorioretinal biomarkers in optical coherence tomography scans: a deep learning approach. IEEE Trans Instrum Meas 70:1–17. https://doi.org/10.1109/TIM.2021.3077988
4. Huang W et al (2019) Arterial spin labeling images synthesis from sMRI using unbalanced deep discriminant learning. IEEE Trans Med Imaging 38(10):2338–2351. https://doi.org/10.1109/TMI.2019.2906677
5. Huang L, He X, Fang L, Rabbani H, Chen X (2019) Automatic classification of retinal optical coherence tomography images with layer-guided convolutional neural network. IEEE Signal Process Lett 26(7):1026–1030
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