AI-based support for optical coherence tomography in age-related macular degeneration.

Int J Retina Vitreous

Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.

Published: April 2024

AI Article Synopsis

  • AI is significantly transforming the medical field, particularly in ophthalmology, by utilizing high-resolution imaging data like optical coherence tomography (OCT) to improve diagnosis and treatment.
  • Age-related macular degeneration (AMD) is a leading cause of blindness, affecting about 196 million people globally, and relies heavily on OCT for monitoring and management.
  • AI algorithms have the potential to enhance clinical practice by offering precise and rapid analysis of biomarkers, predicting disease progression, and supporting treatment decisions in both routine care and research studies.

Article Abstract

Artificial intelligence (AI) has emerged as a transformative technology across various fields, and its applications in the medical domain, particularly in ophthalmology, has gained significant attention. The vast amount of high-resolution image data, such as optical coherence tomography (OCT) images, has been a driving force behind AI growth in this field. Age-related macular degeneration (AMD) is one of the leading causes for blindness in the world, affecting approximately 196 million people worldwide in 2020. Multimodal imaging has been for a long time the gold standard for diagnosing patients with AMD, however, currently treatment and follow-up in routine disease management are mainly driven by OCT imaging. AI-based algorithms have by their precision, reproducibility and speed, the potential to reliably quantify biomarkers, predict disease progression and assist treatment decisions in clinical routine as well as academic studies. This review paper aims to provide a summary of the current state of AI in AMD, focusing on its applications, challenges, and prospects.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11000391PMC
http://dx.doi.org/10.1186/s40942-024-00549-1DOI Listing

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