4.5 Review

Artificial intelligence in OCT angiography

Journal

PROGRESS IN RETINAL AND EYE RESEARCH
Volume 85, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.preteyeres.2021.100965

Keywords

OCT Angiography; Artificial intelligence; Deep learning; Image analysis

Categories

Funding

  1. National Institutes of Health [R01 EY027833, R01 EY024544, R01EY031394, R01 EY023285, P30 EY010572]
  2. Unrestricted Departmental Funding Grant, William & Mary Greve Special Scholar Award from Research to Prevent Blindness (New York, NY)
  3. Bright Focus Foundation [G2020168]

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Optical coherence tomographic angiography (OCTA) is a non-invasive imaging technique that provides three-dimensional vascular images, while artificial intelligence (AI) based image analysis can accurately quantify vascular features and pathology in various disease contexts of the eye. This combination shows promise in accurate diagnosis in different disease and eye regions.
Optical coherence tomographic angiography (OCTA) is a non-invasive imaging modality that provides threedimensional, information-rich vascular images. With numerous studies demonstrating unique capabilities in biomarker quantification, diagnosis, and monitoring, OCTA technology has seen rapid adoption in research and clinical settings. The value of OCTA imaging is significantly enhanced by image analysis tools that provide rapid and accurate quantification of vascular features and pathology. Today, the most powerful image analysis methods are based on artificial intelligence (AI). While AI encompasses a large variety of techniques, machinelearning-based, and especially deep-learning-based, image analysis provides accurate measurements in a variety of contexts, including different diseases and regions of the eye. Here, we discuss the principles of both OCTA and AI that make their combination capable of answering new questions. We also review contemporary applications of AI in OCTA, which include accurate detection of pathologies such as choroidal neovascularization, precise quantification of retinal perfusion, and reliable disease diagnosis.

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