Ophthalmic Image Generation using GAN for Branch Retinal Vein Occlusions and Laser Spots


  • Swati Shilaskar Vishwakarma Institute of Technology, Pune, India
  • Shripad Bhatlawande Vishwakarma Institute of Technology, Pune, India
  • Dyuti Bobby Vishwakarma Institute of Technology, Pune, India
  • Atharva Dusane Vishwakarma Institute of Technology, Pune, India
  • Anjali Solanke Marathwada Mitramandal’s College of Engineering, Pune, India


Adversarial networks, Branch Retinal Vein Occlusions, Laser Spots, GANs, Generative Adversarial Networks, Ophthalmic images


This research paper presents a novel methodology for generating ophthalmic images depicting Laser Spots and Branch Retinal Vein Occlusions via the application of Generative Adversarial Networks (GANs). The study's dataset includes images of both Laser Spots and Branch Retinal Vein Occlusions. Prior to GAN model training, the images undergo essential preprocessing steps, involving uniform resizing, and pixel value standardization. The GAN architecture is designed with a generator network and a discriminator network, operating collaboratively to yield images similar to the input samples and appraise their quality, respectively. After preparing the dataset of ophthalmic images, the generator and discriminator network were employed to construct the GAN model. After the model is trained, the generator network is effectively employed to synthesize new ophthalmic images of Laser Spots and Branch Retinal Vein Occlusions. The generated images were evaluated using various metrics such as visual inspection, quantitative analysis, and comparison with existing images. The experimental outcomes demonstrate that the GAN model successfully generates superior-quality ophthalmic images of Laser Spots and Branch Retinal Vein Occlusions, closely resembling the attributes of the input images. The evaluation of Fréchet Inception Distance (FID) scores demonstrates the promising quality of GAN-generated images. The generated images can potentially be used for diagnostic, educational, and research purposes.


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How to Cite

Shilaskar, S. ., Bhatlawande, S. ., Bobby, D. ., Dusane, A. ., & Solanke, A. . (2023). Ophthalmic Image Generation using GAN for Branch Retinal Vein Occlusions and Laser Spots. International Journal of Intelligent Systems and Applications in Engineering, 12(2), 336–345. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4257



Research Article