JBiOp/
Articles/
2603003255
  • Open Access
  • Review

Ophthalmic OCT-Based Image Generation Using GANs: A Scoping Review

  • Hadi Afsharan 1, 2, 3, *,   
  • Parmida Ghorbanian 1, 2,   
  • Farzan Navaeipour 1,   
  • Najmeh Fayyazifar 1,   
  • Yiheng Lyu 1, 4,   
  • Mohammed Bennamoun 4,   
  • Barry Cense 2,   
  • Girish Dwivedi 1, 3, 5

Received: 28 Nov 2025 | Revised: 22 Jan 2026 | Accepted: 09 Mar 2026 | Published: 08 Apr 2026

Abstract

Recent advances in artificial intelligence (AI) and deep learning (DL) are reshaping ophthalmology, particularly in the domains of image analysis and image synthesis. Optical coherence tomography (OCT) has become indispensable for diagnosing and monitoring retinal diseases, and the application of generative models such as generative adversarial networks (GANs) now enables the creation of realistic synthetic OCT data. In this systematic review, we evaluate the current state of OCT image generation using DL techniques, with emphasis on retinal applications including common pathologies such as age-related macular degeneration, diabetic retinopathy, glaucoma, diabetic retinopathy and other retinal pathologies. We provide an overview of commonly employed architectures, including GAN variants, variational autoencoders, and emerging diffusion models, and highlight how they have been applied for data augmentation, cross-modality translation, noise reduction, and rare pathology synthesis. We discuss validation strategies, performance metrics, and limitations across existing studies, and emphasize the clinical opportunities these technologies present in improving diagnostic accuracy, education, and accessibility of advanced imaging. Finally, we identify gaps in dataset diversity, external validation, and regulatory considerations, and outline future directions to ensure responsible translation of synthetic OCT imaging into clinical practice.

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Supplementary Materials
DOI
10.53941/jbiop.2026.100001
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Volume 2, Issue 1
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Afsharan, H.; Ghorbanian, P.; Navaeipour, F.; Fayyazifar, N.; Lyu, Y.; Bennamoun, M.; Cense, B.; Dwivedi, G. Ophthalmic OCT-Based Image Generation Using GANs: A Scoping Review. Journal of Bio-optics 2026, 2 (1), 1. https://doi.org/10.53941/jbiop.2026.100001.
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