Research Institute of Visual Computing

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

Authors:  Vedran Kajić,1,2,3,* Marieh Esmaeelpour,4,1 Boris Považay,1 David Marshall,2 Paul L. Rosin,2 and Wolfgang Drexler1,3

DOI: 10.1364/BOE.3.000086

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.

 

Link to Paper

Authors

Prof. Paul Rosin

Prof. Paul Rosin

Various aspects of computer vision, including 2D and 3D facial analysis and synthesis.