Please use this identifier to cite or link to this item:
https://doi.org/10.1364/boe.426093
DC Field | Value | |
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dc.title | Framework for quantitative three-dimensional choroidal vasculature analysis using optical coherence tomography | |
dc.contributor.author | Saxena, Ashish | |
dc.contributor.author | Yao, Xinwen | |
dc.contributor.author | Wong, Damon | |
dc.contributor.author | Chua, Jacqueline | |
dc.contributor.author | Ang, Marcus | |
dc.contributor.author | Hoang, Quan, V | |
dc.contributor.author | Agrawal, Rupesh | |
dc.contributor.author | Girard, Michael | |
dc.contributor.author | Cheung, Gemmy | |
dc.contributor.author | Schmetterer, Leopold | |
dc.contributor.author | Tan, Bingyao | |
dc.date.accessioned | 2022-10-12T08:04:26Z | |
dc.date.available | 2022-10-12T08:04:26Z | |
dc.date.issued | 2021-07-19 | |
dc.identifier.citation | Saxena, Ashish, Yao, Xinwen, Wong, Damon, Chua, Jacqueline, Ang, Marcus, Hoang, Quan, V, Agrawal, Rupesh, Girard, Michael, Cheung, Gemmy, Schmetterer, Leopold, Tan, Bingyao (2021-07-19). Framework for quantitative three-dimensional choroidal vasculature analysis using optical coherence tomography. Biomedical Optics Express 12 (8) : 4982-4996. ScholarBank@NUS Repository. https://doi.org/10.1364/boe.426093 | |
dc.identifier.issn | 2156-7085 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/232434 | |
dc.description.abstract | Choroidal vasculature plays an important role in the pathogenesis of retinal diseases, such asmyopic maculopathy, age-related macular degeneration, diabetic retinopathy, central serous chorioretinopathy, and ocular inflammatory diseases. Current optical coherence tomography (OCT) technology provides three-dimensional visualization of the choroidal angioarchitecture; however, quantitative measures remain challenging. Here, we propose and validate a framework to segment and quantify the choroidal vasculature from a prototype swept-source OCT (PLEX Elite 9000, Carl Zeiss Meditec, USA) using a 3×3 mm scan protocol centered on the macula. Enface images referenced from the retinal pigment epithelium were reconstructed from the volumetric data. The boundaries of the choroidal volume were automatically identified by tracking the choroidal vessel feature structure over the depth, and a selective sliding window was applied for segmenting the vessels adaptively from attenuation-corrected enface images. We achieved a segmentation accuracy of 96% ± 1% as compared with manual annotation, and a dice coefficient of 0.83 ± 0.04 for repeatability. Using this framework on both control (0.00 D to -2.00 D) and highly myopic (-8.00 D to -11.00 D) eyes, we report a decrease in choroidal vessel volume (p<0.001) in eyes with high myopia. © 2021 Optical Society of America. | |
dc.publisher | The Optical Society | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | Scopus OA2021 | |
dc.type | Article | |
dc.contributor.department | DUKE-NUS MEDICAL SCHOOL | |
dc.contributor.department | DEAN'S OFFICE (DUKE-NUS MEDICAL SCHOOL) | |
dc.contributor.department | DUKE-NUS OFFICE OF ACAD & CLINICAL DEVT | |
dc.description.doi | 10.1364/boe.426093 | |
dc.description.sourcetitle | Biomedical Optics Express | |
dc.description.volume | 12 | |
dc.description.issue | 8 | |
dc.description.page | 4982-4996 | |
Appears in Collections: | Staff Publications Elements |
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