ArticleOptometry and vision science : official publication of the American Academy of Optometry2016
Validation of Macular Choroidal Thickness Measurements from Automated SD-OCT Image Segmentation.
Article in Optometry and vision science : official publication of the American Academy of Optometry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed, 23 citations in OpenAlex.
- Three-Year Change in Subfoveal Choroidal Thickness and Area With Multifocal Contact Lens Wear in the Bifocal Lenses in Nearsighted Kids (BLINK) Study.Investigative ophthalmology & visual science · 2025Trial
- Bifocal & Atropine in Myopia Study: Baseline Data and Methods.Optometry and vision science : official publication of the American Academy of Optometry · 2019Trial
- Segmentation of choroidal area in optical coherence tomography images using a transfer learning-based conventional neural network: a focus on diabetic retinopathy and a literature review.BMC medical imaging · 2024Review
- Choroidal Thickness in Different Patterns of Diabetic Macular Edema.Journal of clinical medicine · 2022Article
- An Update on Choroidal Layer Segmentation Methods in Optical Coherence Tomography Images: a Review.Journal of biomedical physics & engineering · 2022Review
- Choroidal Volume Evaluation after Photodynamic Therapy Using New Optical Coherence Tomography Imaging Algorithm.Pharmaceuticals (Basel, Switzerland) · 2021Article
- A metrological approach to the analysis of choroidal thickness by optical coherence tomography 3D scans in myopia research.Scientific reports · 2019Article
- Automatic choroidal segmentation in OCT images using supervised deep learning methods.Scientific reports · 2019Article
- Inter- and intraobserver repeatability and reproducibility of choroidal thickness measurements using two different methods.International ophthalmology · 2019Article
- Repeatability of choroidal thickness measurements with Spectralis OCT images.BMJ open ophthalmology · 2019Article
- Automatic Choroidal Segmentation in Optical Coherence Tomography Images Based on Curvelet Transform and Graph Theory.Journal of medical signals and sensorsArticle
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
purposeSpectral domain optical coherence tomography (SD-OCT) imaging permits in vivo visualization of the choroid with micron-level resolution over wide areas and is of interest for studies of ocular growth and myopia control. We evaluated the speed, repeatability, and accuracy of a new image segmentation method to quantify choroid thickness compared to manual segmentation.
methodsTwo macular volumetric scans (25 × 30°) were taken from 30 eyes of 30 young adult subjects in two sessions, 1 hour apart. A single rater manually delineated choroid thickness as the distance between Bruch's membrane and sclera across three B-scans (foveal, inferior, and superior-most scan locations). Manual segmentation was compared to an automated method based on graph theory, dynamic programming, and wavelet-based texture analysis. Segmentation performance comparisons included processing speed, choroid thickness measurements across the foveal horizontal midline, and measurement repeatability (95% limits of agreement (LoA)).
resultsSubjects were healthy young adults (n = 30; 24 ± 2 years; mean ± SD; 63% female) with spherical equivalent refractive error of -3.46 ± 2.69D (range: +2.62 to -8.50D). Manual segmentation took 200 times longer than automated segmentation (780 vs. 4 seconds). Mean choroid thickness at the foveal center was 263 ± 24 μm (manual) and 259 ± 23 μm (automated), and this difference was not significant (p = 0.10). Regional segmentation errors across the foveal horizontal midline (±15°) were ≤9 μm (median) except for nasal-most regions closest to the nasal peripapillary margin-15 degrees (19 μm) and 12 degrees (16 μm) from the foveal center. Repeatability of choroidal thickness measurements had similar repeatability between segmentation methods (manual LoA: ±15 μm; automated LoA: ±14 μm).
conclusionsAutomated segmentation of SD-OCT data by graph theory and dynamic programming is a fast, accurate, and reliable method to delineate the choroid. This approach will facilitate longitudinal studies evaluating changes in choroid thickness in response to novel optical corrections and in ocular disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.