Tags

Type your tag names separated by a space and hit enter

Artificial intelligence in OCT angiography.
Prog Retin Eye Res. 2021 Mar 22 [Online ahead of print]PR

Abstract

Optical coherence tomographic angiography (OCTA) is a non-invasive imaging modality that provides three-dimensional, 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, machine-learning-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.

Authors+Show Affiliations

Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA.Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA.Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA.Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA.Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA.Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, 97239, USA. Electronic address: jiaya@ohsu.edu.

Pub Type(s)

Journal Article
Review

Language

eng

PubMed ID

33766775

Citation

Hormel, Tristan T., et al. "Artificial Intelligence in OCT Angiography." Progress in Retinal and Eye Research, 2021, p. 100965.
Hormel TT, Hwang TS, Bailey ST, et al. Artificial intelligence in OCT angiography. Prog Retin Eye Res. 2021.
Hormel, T. T., Hwang, T. S., Bailey, S. T., Wilson, D. J., Huang, D., & Jia, Y. (2021). Artificial intelligence in OCT angiography. Progress in Retinal and Eye Research, 100965. https://doi.org/10.1016/j.preteyeres.2021.100965
Hormel TT, et al. Artificial Intelligence in OCT Angiography. Prog Retin Eye Res. 2021 Mar 22;100965. PubMed PMID: 33766775.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Artificial intelligence in OCT angiography. AU - Hormel,Tristan T, AU - Hwang,Thomas S, AU - Bailey,Steven T, AU - Wilson,David J, AU - Huang,David, AU - Jia,Yali, Y1 - 2021/03/22/ PY - 2020/11/30/received PY - 2021/03/09/revised PY - 2021/03/15/accepted PY - 2022/09/22/pmc-release PY - 2021/3/27/pubmed PY - 2021/3/27/medline PY - 2021/3/26/entrez KW - Artificial intelligence KW - Deep learning KW - Image analysis KW - OCT Angiography SP - 100965 EP - 100965 JF - Progress in retinal and eye research JO - Prog Retin Eye Res N2 - Optical coherence tomographic angiography (OCTA) is a non-invasive imaging modality that provides three-dimensional, 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, machine-learning-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. SN - 1873-1635 UR - https://www.unboundmedicine.com/medline/citation/33766775/Artificial_intelligence_in_OCT_angiography. L2 - https://linkinghub.elsevier.com/retrieve/pii/S1350-9462(21)00026-4 DB - PRIME DP - Unbound Medicine ER -
Try the Free App:
Prime PubMed app for iOS iPhone iPad
Prime PubMed app for Android
Prime PubMed is provided
free to individuals by:
Unbound Medicine.