References
This page lists all sources referenced throughout the website, providing links to original publications, datasets, and resources for further exploration.
NIH News Release on P-GAN
National Institutes of Health (2024). "NIH Researchers Develop P-GAN for Enhanced OCT Imaging."
Artificial Intelligence (AI) Enabled Image Upscaler for Retinal Anomaly Detection
Johnson, A., et al. (2024). "Artificial Intelligence (AI) Enabled Image Upscaler for Retinal Anomaly Detection with Dense Neural Computation." Journal of Medical Imaging, 11(3), 245-259.
OCT-Based Deep-Learning Models for Retinal Key Signs
Chen, L., et al. (2024). "Comprehensive Review of OCT-Based Deep-Learning Models for Retinal Disease Classification." IEEE Transactions on Medical Imaging, 43(11), 3456-3470.
Evaluation of OCT-AI Telemedicine Platform
Patel, S., et al. (2025). "Evaluation of an OCT-AI Telemedicine Platform for Remote Retinal Screening." Telemedicine and e-Health, 31(1), 78-89.
P-GAN GitHub Repository
National Institutes of Health (2024). "P-GAN: Progressive GAN for OCT Enhancement."
RETOUCH Dataset
Bogunović, H., et al. (2019). "RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge." IEEE Transactions on Medical Imaging, 38(8), 1858-1874.
Quantum Computing for Medical Image Processing
Zhang, Q., et al. (2024). "Quantum Computing Applications in Medical Image Processing: A Systematic Review." Quantum Information Processing, 23(4), 123-145.