Adaptive cluster-based superpixel segmentation and BMWMMBO-based DCNN classification for glaucoma detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-023-02751-4.pdf
Reference49 articles.
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3. Wang, T., Ji, Z., Sun, Q., Chen, Q., Shengchen, Y., Fan, W., Yuan, S., Liu, Q.: ‘Label propagation and higher-order constraint-based segmentation of fluid-associated regions in retinal SD-OCT images. Inf. Sci. J. 358–359, 92–111 (2016)
4. Balakrishnan, U.: NDC-IVM: An automatic segmentation of optic disc and cup region from medical images for glaucoma detection. J. Innov. Opt. Health Sci. 10(3), 1–15 (2017)
5. Gómez-Valverde, J.J., Antón, A., Fatti, G., Liefers, B., Herranz, A., Santos, A., Ledesma-Carbayo, M.J.: Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning. Biomed. Opt. Express 10(2), 892–913 (2019)
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