Journal article
Segmentation of anterior segment boundaries in swept source OCT images
Biocybernetics and Biomedical Engineering, Vol.41(3), pp.903-915
2021
Abstract
Quantification of the eye's anterior segment morphology from optical coherence tomography (OCT) images is crucial for research and clinical decision-making, including the diagnosis and monitoring of many ocular diseases. Structural parameters, such as tissue thickness and area are the most common metrics used to quantify these medical images, and tissue segmentation is required before these metrics can be extracted. Currently, swept source OCTallows the capture of cross-sectional images that encompass the entire anterior segment with a high level of detail. However, the manual annotation of tissue boundaries is time-consuming. In this work, an algorithm based on graph-search theory combined with boundary-specific image transformation is applied for the segmentation of anterior segment OCT images. We demonstrate that the method can reliably segment 5 different tissue boundaries in healthy eyes with low boundary error (mean error below 1 pixel across all boundaries). The technique can be used to extract clinically relevant parameters such as central corneal and crystalline lens thickness as well as anterior chamber depth and area, with a high level of agreement with manual segmentation (normalized errors below 1.6%). The proposed method provides a tool that can support clinical and research OCT data analysis.
Details
- Title
- Segmentation of anterior segment boundaries in swept source OCT images
- Authors
- Yoel Garcia Marin (Corresponding Author) - Queensland University of TechnologyMarta Skrok (Author) - Wrocław University of Science and TechnologyDamian Siedlecki (Author) - Wrocław University of Science and TechnologyStephen J. Vincent (Author) - Queensland University of TechnologyMichael J. Collins (Author) - Queensland University of TechnologyDavid Alonso-Caneiro (Author) - Queensland University of Technology
- Publication details
- Biocybernetics and Biomedical Engineering, Vol.41(3), pp.903-915
- Publisher
- Elsevier BV
- DOI
- 10.1016/j.bbe.2021.06.002
- Grant note
- National Health & Medical Research Council Ideas Grant (APP1186915, DAC), Rebecca L. Cooper 2018 Project Grant (DAC).
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99972397602621
- Output Type
- Journal article
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- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Engineering, Biomedical
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Source: InCites