TY - JOUR
T1 - Generative artificial intelligence in ophthalmology
AU - Waisberg, Ethan
AU - Ong, Joshua
AU - Kamran, Sharif Amit
AU - Masalkhi, Mouayad
AU - Paladugu, Phani
AU - Zaman, Nasif
AU - Lee, Andrew G.
AU - Tavakkoli, Alireza
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Generative artificial intelligence (AI) has revolutionized medicine over the past several years. A generative adversarial network (GAN) is a deep learning framework that has become a powerful technique in medicine, particularly in ophthalmology for image analysis. In this paper we review the current ophthalmic literature involving GANs, and highlight key contributions in the field. We briefly touch on ChatGPT, another application of generative AI, and its potential in ophthalmology. We also explore the potential uses for GANs in ocular imaging, with a specific emphasis on 3 primary domains: image enhancement, disease identification, and generating of synthetic data. PubMed, Ovid MEDLINE, Google Scholar were searched from inception to October 30, 2022, to identify applications of GAN in ophthalmology. A total of 40 papers were included in this review. We cover various applications of GANs in ophthalmic-related imaging including optical coherence tomography, orbital magnetic resonance imaging, fundus photography, and ultrasound; however, we also highlight several challenges that resulted in the generation of inaccurate and atypical results during certain iterations. Finally, we examine future directions and considerations for generative AI in ophthalmology.
AB - Generative artificial intelligence (AI) has revolutionized medicine over the past several years. A generative adversarial network (GAN) is a deep learning framework that has become a powerful technique in medicine, particularly in ophthalmology for image analysis. In this paper we review the current ophthalmic literature involving GANs, and highlight key contributions in the field. We briefly touch on ChatGPT, another application of generative AI, and its potential in ophthalmology. We also explore the potential uses for GANs in ocular imaging, with a specific emphasis on 3 primary domains: image enhancement, disease identification, and generating of synthetic data. PubMed, Ovid MEDLINE, Google Scholar were searched from inception to October 30, 2022, to identify applications of GAN in ophthalmology. A total of 40 papers were included in this review. We cover various applications of GANs in ophthalmic-related imaging including optical coherence tomography, orbital magnetic resonance imaging, fundus photography, and ultrasound; however, we also highlight several challenges that resulted in the generation of inaccurate and atypical results during certain iterations. Finally, we examine future directions and considerations for generative AI in ophthalmology.
KW - AI
KW - Artificial ophthalmic image synthesis
KW - ChatGPT
KW - Deep learning
KW - GPT4
KW - Generative adversarial networks
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85199192424&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85199192424&partnerID=8YFLogxK
U2 - 10.1016/j.survophthal.2024.04.009
DO - 10.1016/j.survophthal.2024.04.009
M3 - Review article
C2 - 38762072
AN - SCOPUS:85199192424
SN - 0039-6257
VL - 70
SP - 1
EP - 11
JO - Survey of Ophthalmology
JF - Survey of Ophthalmology
IS - 1
ER -