Automated choroidal segmentation of 1060 nm OCT in healthy and pathologic eyes using a statistical model

Kajic, Vedran, Esmaeelpour Hajyar, Marieh, Povazay, Boris, Marshall, Andrew David ORCID: https://orcid.org/0000-0003-2789-1395, Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884 and Drexler, Wolfgang 2012. Automated choroidal segmentation of 1060 nm OCT in healthy and pathologic eyes using a statistical model. Biomedical Optics Express 3 (1) , pp. 86-103. 10.1364/BOE.3.000086

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Abstract

A two stage statistical model based on texture and shape for fully automatic choroidal segmentation of normal and pathologic eyes obtained by a 1060 nm optical coherence tomography (OCT) system is developed. A novel dynamic programming approach is implemented to determine location of the retinal pigment epithelium/ Bruch’s membrane /choriocapillaris (RBC) boundary. The choroid–sclera interface (CSI) is segmented using a statistical model. The algorithm is robust even in presence of speckle noise, low signal (thick choroid), retinal pigment epithelium (RPE) detachments and atrophy, drusen, shadowing and other artifacts. Evaluation against a set of 871 manually segmented cross-sectional scans from 12 eyes achieves an average error rate of 13%, computed per tomogram as a ratio of incorrectly classified pixels and the total layer surface. For the first time a fully automatic choroidal segmentation algorithm is successfully applied to a wide range of clinical volumetric OCT data.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Optometry and Vision Sciences Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RE Ophthalmology
Additional Information:	Pdf uploaded in accordance with publisher's policy at http://www.sherpa.ac.uk/romeo/issn/2156-7085/ (accessed 24/04/2014).
Publisher:	OSA
ISSN:	2156-7085
Date of First Compliant Deposit:	30 March 2016
Last Modified:	06 Apr 2024 17:14
URI:	https://orca.cardiff.ac.uk/id/eprint/27585

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