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Artificial Intelligence in Retinal Vascular Imaging

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Retinal Vascular Disease

Part of the book series: Retina Atlas ((RA))

Abstract

Artificial intelligence (AI) has flourished in the last decade due to the emergence of deep learning, a class of machine learning algorithms dedicated to building large artificial neural network models capable of learning through exposure to large amounts of data. Ophthalmology, and especially retinal science, are at the forefront of AI applications in medicine, with a fully autonomous AI image-based diagnostic system that has recently been approved by the FDA as a first of its kind in medicine (Abramoff et al. 2018; Topol 2019).

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Authors and Affiliations

  1. Department of Ophthalmology, Medical University of Vienna, Vienna, Austria

    Ursula Schmidt-Erfurth, Sophie Riedl, Martin Michl & Hrvoje Bogunović

Authors
  1. Ursula Schmidt-Erfurth
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  2. Sophie Riedl
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  3. Martin Michl
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  4. Hrvoje Bogunović
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Corresponding author

Correspondence to Ursula Schmidt-Erfurth .

Editor information

Editors and Affiliations

  1. New York Eye and Ear Infirmary of Mount Sinai, New York, NY, USA

    Alan Sheyman

  2. Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Amani A. Fawzi

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Schmidt-Erfurth, U., Riedl, S., Michl, M., Bogunović, H. (2020). Artificial Intelligence in Retinal Vascular Imaging. In: Sheyman, A., Fawzi, A.A. (eds) Retinal Vascular Disease. Retina Atlas. Springer, Singapore. https://doi.org/10.1007/978-981-15-4075-2_13

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  • DOI: https://doi.org/10.1007/978-981-15-4075-2_13

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  • Print ISBN: 978-981-15-4074-5

  • Online ISBN: 978-981-15-4075-2

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