The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Automated Identification of Diabetic Retinopathy Stages Using Digital Fundus Images
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Citations
Cites
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
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Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(1993) · Proceedings of IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1993.341010 · Cited by 14,265
(2007) · Developments in Ophthalmology · doi:10.1159/isbn.978-3-318-01439-6 · Cited by 5,583
Digital Image Processing: PIKS Inside
Pratt, W. K. (2002) · Wiley eBooks · doi:10.1002/0471221325 · Cited by 4,340
(1985) · Archives of Ophthalmology · doi:10.1001/archopht.1985.01050120030015 · Cited by 2,540
Detection of blood vessels in retinal images using two-dimensional matched filters
Chaudhuri, S., Chatterjee, S., Katz, N., Nelson, M., & Goldbaum, M. (1989) · IEEE Transactions on Medical Imaging · doi:10.1109/42.34715 · Cited by 1,668
(1998) · Lecture Notes in Computer Science · doi:10.1007/bfb0056181 · Cited by 1,577
Digital Image Processing, Third Edition
Gonzalez, R. C., Woods, R. E., & Masters, B. R. (2009) · Journal of Biomedical Optics · doi:10.1117/1.3115362 · Cited by 1,367
Walter, T., Klein, J., Massin, P., & Erginay, A. (2002) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2002.806290 · Cited by 825
Cited by
Convolutional Neural Networks for Diabetic Retinopathy
Pratt, H., Coenen, F., Broadbent, D. M., Harding, S. P., & Zheng, Y. (2016) · Procedia Computer Science · doi:10.1016/j.procs.2016.07.014 · Cited by 988
Maheshwari, S., Pachori, R. B., & Acharya, U. R. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2544961 · Cited by 283
Computer-based detection of diabetes retinopathy stages using digital fundus images
Acharya, U. R., Lim, C. M., Ng, E. Y. K., Chee, C., & Tamura, T. (2009) · Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine · doi:10.1243/09544119jeim486 · Cited by 217
Self-citationArtificial Intelligence Methodologies and Their Application to Diabetes
Rigla, M., García-Sáez, G., Pons, B., & Hernando, M. E. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296817710475 · Cited by 131
Semi‐supervised classification of fundus images combined with CNN and GCN
Duan, S., Huang, P., Chen, M., Wang, T., Sun, X., Chen, M., Dong, X., Jiang, Z., & Li, D. (2022) · Journal of Applied Clinical Medical Physics · doi:10.1002/acm2.13746 · Cited by 29
Metadata
- Authors
- Nayak, J., Bhat, P. S., Acharya U, R., Lim, C. M., & Kagathi, M.
- Venue
- Journal of Medical Systems
- Published
- 2007-11-13
- Volume
- 32
- Issue
- 2
- Pages
- 107-115
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- OpenAlex
- W2024978699
- Cited by
- 272
- References
- 33
- FWCI
- 3.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Automated Identification of Diabetic Retinopathy Stages Using Digital Fundus Images. https://app.cochat.ai/papers/10.1007/s10916-007-9113-9
- The paper
- Nayak, J., Bhat, P. S., Acharya U, R., Lim, C. M., & Kagathi, M. (2008). Automated Identification of Diabetic Retinopathy Stages Using Digital Fundus Images. Journal of Medical Systems. https://doi.org/10.1007/s10916-007-9113-9
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
