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Published VersionCC BY V4.0, Open Access
Journal article
Automatic segmentation of choroidal thickness in optical coherence tomography
Biomedical Optics Express, Vol.4(12), pp.2795-2812
2013
PMCID: PMC3862153
PMID: 24409381
Abstract
The assessment of choroidal thickness from optical coherence tomography (OCT) images of the human choroid is an important clinical and research task, since it provides valuable information regarding the eye's normal anatomy and physiology, and changes associated with various eye diseases and the development of refractive error. Due to the time consuming and subjective nature of manual image analysis, there is a need for the development of reliable objective automated methods of image segmentation to derive choroidal thickness measures. However, the detection of the two boundaries which delineate the choroid is a complicated and challenging task, in particular the detection of the outer choroidal boundary, due to a number of issues including: (i) the vascular ocular tissue is non-uniform and rich in non-homogeneous features, and (ii) the boundary can have a low contrast. In this paper, an automatic segmentation technique based on graph-search theory is presented to segment the inner choroidal boundary (ICB) and the outer choroidal boundary (OCB) to obtain the choroid thickness profile from OCT images. Before the segmentation, the B-scan is pre-processed to enhance the two boundaries of interest and to minimize the artifacts produced by surrounding features. The algorithm to detect the ICB is based on a simple edge filter and a directional weighted map penalty, while the algorithm to detect the OCB is based on OCT image enhancement and a dual brightness probability gradient. The method was tested on a large data set of images from a pediatric (1083 B-scans) and an adult (90 B-scans) population, which were previously manually segmented by an experienced observer. The results demonstrate the proposed method provides robust detection of the boundaries of interest and is a useful tool to extract clinical data.
Details
- Title
- Automatic segmentation of choroidal thickness in optical coherence tomography
- Authors
- David Alonso-Caneiro (Corresponding Author) - Queensland University of TechnologyScott A. Read (Author) - Queensland University of TechnologyMichael J. Collins (Author) - Queensland University of Technology
- Publication details
- Biomedical Optics Express, Vol.4(12), pp.2795-2812
- Publisher
- Optica
- Date published
- 2013
- DOI
- 10.1364/BOE.4.002795
- ISSN
- 2156-7085
- PMID
- 24409381; PMC3862153
- Copyright note
- © 2013 Optical Society of America. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99972394002621
- Output Type
- Journal article
Metrics
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InCites Highlights
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- Web Of Science research areas
- Biochemical Research Methods
- Optics
- Radiology, Nuclear Medicine & Medical Imaging
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Source: InCites