An end-to-end network for segmenting the vasculature of three retinal capillary plexuses from OCT angiographic volumes Article Swipe
Yukun Guo
,
Tristan T. Hormel
,
Shaohua Pi
,
Xiang Wei
,
Min Gao
,
John C. Morrison
,
Yali Jia
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1364/boe.431888
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1364/boe.431888
The segmentation of en face retinal capillary angiograms from volumetric optical coherence tomographic angiography (OCTA) usually relies on retinal layer segmentation, which is time-consuming and error-prone. In this study, we developed a deep-learning-based method to segment vessels in the superficial vascular plexus (SVP), intermediate capillary plexus (ICP), and deep capillary plexus (DCP) directly from volumetric OCTA data. The method contains a three-dimensional convolutional neural network (CNN) for extracting distinct retinal layers, a custom projection module to generate three vascular plexuses from OCTA data, and three parallel CNNs to segment vasculature. Experimental results on OCTA data from rat eyes demonstrated the feasibility of the proposed method. This end-to-end network has the potential to simplify OCTA data processing on retinal vasculature segmentation. The main contribution of this study is that we propose a custom projection module to connect retinal layer segmentation and vasculature segmentation modules and automatically convert data from three to two dimensions, thus establishing an end-to-end method to segment three retinal capillary plexuses from volumetric OCTA without any human intervention.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1364/boe.431888
- OA Status
- gold
- Cited By
- 28
- References
- 49
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3179482093
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3179482093Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1364/boe.431888Digital Object Identifier
- Title
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An end-to-end network for segmenting the vasculature of three retinal capillary plexuses from OCT angiographic volumesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-07-06Full publication date if available
- Authors
-
Yukun Guo, Tristan T. Hormel, Shaohua Pi, Xiang Wei, Min Gao, John C. Morrison, Yali JiaList of authors in order
- Landing page
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https://doi.org/10.1364/boe.431888Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1364/boe.431888Direct OA link when available
- Concepts
-
Retinal, Segmentation, Computer science, Artificial intelligence, Convolutional neural network, Projection (relational algebra), Plexus, Anatomy, Computer vision, Medicine, Ophthalmology, AlgorithmTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
28Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 6, 2024: 9, 2023: 10, 2022: 2, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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49Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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