The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Optic disc and cup segmentation methods for glaucoma detection with modification of U-Net convolutional neural network
Open accessAbstract
Glaucoma is the second leading cause of blindness all over the world, with approximately 60 million cases reported worldwide in 2010. If undiagnosed in time, glaucoma causes irreversible damage to the optic nerve leading to blindness. The optic nerve head examination, which involves measurement of cup-todisc ratio, is considered one of the most valuable methods of structural diagnosis of the disease. Estimation of cup-to-disc ratio requires segmentation of optic disc and optic cup on eye fundus images and can be performed by modern computer vision algorithms. This work presents universal approach for automatic optic disc and cup segmentation, which is based on deep learning, namely, modification of U-Net convolutional neural network. Our experiments include comparison with the best known methods on publicly available databases DRIONS-DB, RIM-ONE v.3, DRISHTI-GS. For both optic disc and cup segmentation, our method achieves quality comparable to current state-of-the-art methods, outperforming them in terms of the prediction time.
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Cites
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2012) · arXiv · doi:10.48550/arxiv.1207.0580 · Cited by 6,382
Lodhia, V., Karanja, S., Lees, S., & Bastawrous, A. (2016) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4746 · Cited by 86
Cited by
Orlando, J. I., Fu, H., Barbosa Breda, J., van Keer, K., Bathula, D. R., Diaz-Pinto, A., Fang, R., Heng, P.-A., Kim, J., Lee, J., et al. (2020) · Medical Image Analysis · doi:10.1016/j.media.2019.101570 · Cited by 855
Lee, D., Lee, W. H., Seo, H. G., Oh, B.-M., Lee, J. C., & Kim, H. C. (2020) · IEEE Access · doi:10.1109/access.2020.3019532 · Cited by 22
Metadata
- Authors
- Sevastopolsky, A.
- Venue
- Pattern Recognition and Image Analysis
- Publisher
- Pleiades Publishing Ltd
- Published
- 2017-07
- Volume
- 27
- Issue
- 3
- Pages
- 618-624
- ISSN
- 1054-6618 (ISSN-L)
- 1555-6212
- OpenAlex
- W2607394097
- Cited by
- 432
- References
- 3
- FWCI
- 29.35
- Type
- journal article
- Language
- en
- Open access
- green
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- Sevastopolsky, A. (2017). Optic disc and cup segmentation methods for glaucoma detection with modification of U-Net convolutional neural network. Pattern Recognition and Image Analysis. https://doi.org/10.1134/s1054661817030269
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