Automatic segmentation of choroidal thickness in optical coherence tomography

Alonso-Caneiro, David, Read, Scott A., & Collins, Michael J. (2013) Automatic segmentation of choroidal thickness in optical coherence tomography. Biomedical Optics Express, 4(12), pp. 2795-2812.

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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.

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23 citations in Scopus
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18 citations in Web of Science®

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88 since deposited on 12 Nov 2013
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ID Code: 64252
Item Type: Journal Article
Refereed: Yes
Keywords: Image processing, Choroid segmentation, Optical Coherence Tomography
DOI: 10.1364/BOE.4.002795
ISSN: 2156-7085
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > BIOMEDICAL ENGINEERING (090300) > Biomechanical Engineering (090302)
Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > OPTOMETRY AND OPHTHALMOLOGY (111300) > Optometry and Ophthalmology not elsewhere classified (111399)
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Optometry & Vision Science
Deposited On: 12 Nov 2013 05:11
Last Modified: 10 Apr 2014 23:45

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