Segmentation-Driven Morphology-Guided Attention Mechanism for Rhegmatogenous Retinal Detachment Classification
References
- Gan, F., Q. Wan, H. Fan, W. Chen, W. Qin, X. Li, T. Liu, J. Cao, Z. You. Automatic Classification of Retinal Detachment Using a Deep Transfer Learning Algorithm Based on Multimodal Fundus Images: A Multicenter Study. – Ophthalmic Epidemiology, 2024.
- Lake, S. R., M. J. Bottema, T. Lange, K. A. Williams, K. J. Reynolds. Swept-Source OCT Mid-Peripheral Retinal Irregularity in Retinal Detachment and Posterior Vitreous Detachment Eyes. – Bioengineering, Vol. 10, 2023, No 3, 377.
- Al-Dwairi, R., O. Saleh, H. Mohidat, S. AlBeiruti, A. Alshami, L. ElTaani, A. Sharayah, A. H. AlSharie, A. Aleshawi. Characteristics, Risks, and Prevention of Rhegmatogenous Retinal Detachment in the Contralateral Eye. – Journal of Clinical Medicine, Vol. 14, 2025, No 1, 222.
- Sharmin, S., M. R. Rashid, T. Khatun, M. Z. Hasan, M. S. Uddin. A Dataset of Color Fundus Images for the Detection and Classification of Eye Diseases. – Data in Brief, Vol. 57, 2024, 110979.
- Ferrara, M., M. Al-Zubaidy, A. Song, P. Avery, D. A. Laidlaw, T. H. Williamson, D. Yorston, D. H. Steel. The Effect of Age on Phenotype of Primary Rhegmatogenous Retinal Detachment. – Eye, Vol. 37, 2023, No 6, pp. 1114-1122.
- Motta, L., R. Frisina, M. Ripa, I. Gius, A. Greggio, L. Tozzi, G. DeSalvo, A. Meduri. Postoperative Complications after Successful Primary Rhegmatogenous Retinal Detachment Repair. – BMC Ophthalmology, Vol. 23, 2023, No 1, 77.
- Choovuthayakorn, J., P. Rajsirisongsri, D. Patikulsila, O. Nanegrungsunk, V. Chaikitmongkol, S. Seetasut, Y. Tantivit, N. Krisanuruks, A. Sangkaew, P. Tangkitchot, A. Apivatthakakul, P. Kunavisarut. Characteristics and Surgical Outcomes of Giant Retinal Tear Associated Rhegmatogenous Retinal Detachment. – Scientific Reports, Vol. 14, 2024, No 1, 19943.
- Oquendo, P. L., G. S. Sodhi, S. C. Naidu, I. M. Melo, A. Pecaku, S. Demian, P. J. Belin, W. W. Lee, P. G. Christakis, H. Hamli, A. Bansal. Optical Coherence Tomography Features in Fovea-Off Exudative vs Rhegmatogenous Retinal Detachment. – American Journal of Ophthalmology, Vol. 268, 2024, pp. 212-221.
- Pecaku, A., S. C. Naidu, S. Demian, M. C. Pimentel, I. M. Melo, R. H. Muni. Morphologic Features of Regulated vs. Dysregulated Rhegmatogenous Retinal Detachment Using Swept-Source Optical Coherence Tomography. – American Journal of Ophthalmology, Vol. 268, 2024, pp. 19-28.
- Barioulet, L., M. Rueter, V. Sentis, P. Fournié, S. Mrozek, D. Méligne, G. Moulis, A. Sommet, V. Soler. Meteorological Factors and Rhegmatogenous Retinal Detachment in Metropolitan France. – Scientific Reports, Vol. 14, 2024, No 1, 18857.
- Schöneberger, V., J. Q. Li, L. Menghesha, F. G. Holz, F. Schaub, T. U. Krohne. Outcomes of Short-Versus Long-Acting Gas Tamponades in Vitrectomy for Rhegmatogenous Retinal Detachment. – International Journal of Retina and Vitreous, Vol. 10, 2024, No 1, 16.
- Hosni, S., H. Khachnaoui, H. M. Zgolli, S. Mabrouk, D. Sidibé, H. Tabia, N. Khlifa. Prediction of Postoperative Visual Acuity in Rhegmatogenous Retinal Detachment Using OCT Images. – IEEE Access, Vol. 11, 2023, pp. 135435-135448.
- Garneau, J., M. Hébert, E. You, A. Lachance, S. Bourgault, M. Caissie, É. Tourville, A. Dirani. Outcomes of Surgical Repair of Retinoschisis-Associated Retinal Detachment Compared to Rhegmatogenous Retinal Detachment. – BMC Ophthalmology, Vol. 22, 2022, No 1, 10.
- Kovács, L., G. Szabó. B-Morpher: Automated Learning of Morphological Language Characteristics for Inflection and Morphological Analysis. – Cybernetics and Information Technologies, Vol. 22, 2022, No 4, pp. 111-128.
- Anitha, E., D. J. Aravindhar. Efficient Retinal Detachment Classification Using Hybrid Machine Learning with Levy Flight-Based Optimization. – Expert Systems with Applications, Vol. 239, 2024, 122311.
- Yadav, S., R. Murugan, S. Mondal, P. Bhattacharjee. GRD-Net: Graph Neural Network Model for Retinal Detachment Classification through Fundus Image. – In: Proc. of IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES’24), 2024, pp. 35-40.
- Yadav, S., R. Murugan, T. Goel. Opti-EN-Net: Optimized Ensemble Deep Neural Network for the Classification of Retinal Detachment through Fundus Images. – Biomedical Signal Processing and Control, Vol. 91, 2024, 105999.
- Li, H., J. Cao, K. You, Y. Zhang, J. Ye. Artificial Intelligence-Assisted Management of Retinal Detachment from Ultra-Widefield Fundus Images Based on a Weakly Supervised Approach. – Frontiers in Medicine, Vol. 11, 2024, 1326004.
- Lake, S. R., M. J. Bottema, K. A. Williams, T. Lange, K. J. Reynolds. Retinal Shape-Based Classification of Retinal Detachment and Posterior Vitreous Detachment Eyes. – Ophthalmology and Therapy, Vol. 12, 2023, No 1, pp. 155-165.
- Li, Z., C. Guo, D. Nie, D. Lin, Y. Zhu, C. Chen, X. Wu, F. Xu, C. Jin, X. Zhang, H. Xiao. Deep Learning for Detecting Retinal Detachment and Discerning Macular Status Using Ultra-Widefield Fundus Images. – Communications Biology, Vol. 3, 2020, No 1, 15.
- Guo, H., C. Ou, G. Wang, B. Lu, X. Li, T. Yang, J. Zhang. Prediction of Visual Outcome after Rhegmatogenous Retinal Detachment Surgery Using Artificial Intelligence Techniques. – Translational Vision Science & Technology, Vol. 13, 2024, No 5, 17.
- Panchal, S., A. Naik, M. Kokare, S. Pachade, R. Naigaonkar, P. Phadnis, A. Bhange. Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0: A Dataset of Frequently and Rarely Identified Diseases. – Data, Vol. 8, 2023, No 2, 29.
- ARMD Dataset (Accessed on July 2025).
- https://www.kaggle.com/datasets/saketlad/armd-combined-dataset-fundus-and-oct
- Tan, M., Q. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. – In: Proc. of International Conference on Machine Learning (PMLR’19), 2019, pp. 6105-6114.
DOI: https://doi.org/10.2478/cait-2026-0030 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702 (formerly 1314-4081)
Language: English
Page range: 142 - 161
Submitted on: Mar 19, 2026
Accepted on: May 25, 2026
Published on: Sep 9, 2026
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Keywords:
Related subjects:
© 2026 Husna Banu, Balaji Prabhu Baluvaneralu Veeranna, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.