- An interpretable dual attention network for diabetic retinopathy grading: IDANet Artificial Intelligence in Medicine, A. Bhati , N. Gour , P. Khanna , A. Ojha , N. Werghi, 2024 [pdf] [Demo]
- Angular contrastive distillation driven self-supervised scanner independent screening and grading of retinopathy. Information Fusion, 2023. T. Hassan, Z Li, MU Akram, I Hussain, K Khalaf, N Werghi. [pdf] [demo]
- Retinopathy Screening from OCT Imagery via Deep Learning. In Data Fusion Techniques and Applications for Smart Healthcare, A. Singh, S. Berretti, Eds, Elsevier, 2024. R. Ahmed, B. Hassan, A. Khane, T. Hassan, J. Dias, M.L. Seghier, N. Werghi. [pdf] [demo]
- Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning. IEEE Trans. on Instrumentation and Measurement, 2021. B. Hassan, T. Hassan, M.U. Akram, S. Hashmi, A. Taguri, N. Werghi. [pdf] [demo]
- Joint Segmentation and Quantification of Chorioretinal Biomarkers in Optical Coherence Tomography Scans: A Deep Learning Approach. IEEE Trans. on Instrumentation and Measurement, 2021. B. Hassan, S. Qin, R. Ahmed, T. Hassan, R.Ahmed, N. Werghi. [pdf] [demo]
- Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy. Computers in Biology and Medicine, 2021. B. Hassan, T. Hassan, N. Werghi. [pdf] [demo]
- CDC-Net: Cascaded decoupled convolutional network for lesion-assisted detection and grading of retinopathy using optical coherence tomography (OCT) scans. Biomedical Signal Processing and Control, 2021. B. Hassan, T. Hassan, N. Werghi. [pdf] [demo]
- RAG-FW: A Hybrid Convolutional Framework for the Automated Extraction of Retinal Lesions and Lesion-influenced Grading of Human Retinal Pathology. IEEE Journal of Biomedical and Health Informatics, 2020. T. Hassan, M. U. Akram, N. Werghi, M. N. Nazir. [pdf] [demo]
- Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression. IEEE Transactions on Biomedical Engineering, 2020. H Raja, T.Hassan, M. Akram, N. Werghi. [pdf] [demo]
- Multi-scale Roughness Approach for Assessing Posterior Capsule Opacification. IEEE Journal of Biomedical and Health Informatics, 18 (6), pp. 1923–1931, 2014. A. Vivekanand, N. Werghi, H. Al-Ahmad. [pdf] [demo]
- An Unsupervised Learning Approach Based on a Hopfield-like Network for Assessing Posterior Capsule Opacification from Digital Images. Pattern Analysis and Applications, 13 (4), pp. 383–396, 2010. N. Werghi, R. Sammouda, F. Alkirbi. [pdf] [demo]