ArticleInvestigative ophthalmology & visual science2016
4D Graph-Based Segmentation for Reproducible and Sensitive Choroid Quantification From Longitudinal OCT Scans.
Article in Investigative ophthalmology & visual science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Generalized 3D registration algorithm for enhancing retinal optical coherence tomography images.Journal of biomedical optics · 2024Article
- Longitudinal deep network for consistent OCT layer segmentation.Biomedical optics express · 2023Article
- Cyst identification in retinal optical coherence tomography images using hidden Markov model.Scientific reports · 2023Article
- Visualization of Mouse Choroidal and Retinal Vasculature Using Fluorescent Tomato Lectin Perfusion.Translational vision science & technology · 2020Article
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Authors and funding
6 authors.
Funding
Abstract
Purpose: Longitudinal imaging is becoming more commonplace for studies of disease progression, response to treatment, and healthy maturation. Accurate and reproducible quantification methods are desirable to fully mine the wealth of data in such datasets. However, most current retinal OCT segmentation methods are cross-sectional and fail to leverage the inherent context present in longitudinal sequences of images. Methods: We propose a novel graph-based method for segmentation of multiple three-dimensional (3D) scans over time (termed 3D + time or 4D). The usefulness of this approach in retinal imaging is illustrated in the segmentation of the choroidal surfaces from longitudinal optical coherence tomography (OCT) scans. A total of 3219 synthetic (3070) and patient (149) OCT images were segmented for validation of our approach. Results: The results show that the proposed 4D segmentation method is significantly more reproducible (P < 0.001) than the 3D approach and is significantly more sensitive to temporal changes (P < 0.0001) achieved by the substantial increase of measurement robustness. Conclusions: This is the first automated 4D method for jointly quantifying choroidal thickness in longitudinal OCT studies. Our method is robust to image noise and produces more reproducible choroidal thickness measurements than a sequence of independent 3D segmentations, without sacrificing sensitivity to temporal changes.
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