Loosely coupled level sets for retinal layers and drusen segmentation in subjects with dry age-related macular degeneration

Conference Paper (2016)
Author(s)

J Novosel (TU Delft - ImPhys/Quantitative Imaging, Rotterdam Eye Hospital)

Ziyuan Wang

Henk De Jong (Rotterdam Eye Hospital)

K.A. Vermeer (Rotterdam Eye Hospital)

L. J. van Vliet (TU Delft - ImPhys/Quantitative Imaging)

Research Group
ImPhys/Quantitative Imaging
Copyright
© 2016 J. Novosel, Ziyuan Wang, Henk de Jong, K.A. Vermeer, L.J. van Vliet
DOI related publication
https://doi.org/10.1117/12.2214698
More Info
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Publication Year
2016
Language
English
Copyright
© 2016 J. Novosel, Ziyuan Wang, Henk de Jong, K.A. Vermeer, L.J. van Vliet
Research Group
ImPhys/Quantitative Imaging
Volume number
9784
Pages (from-to)
1-7
ISBN (print)
9781510600195
Reuse Rights

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Abstract

Optical coherence tomography (OCT) is used to produce high-resolution three-dimensional images of the retina, which permit the investigation of retinal irregularities. In dry age-related macular degeneration (AMD), a chronic eye disease that causes central vision loss, disruptions such as drusen and changes in retinal layer thicknesses occur which could be used as biomarkers for disease monitoring and diagnosis. Due to the topology disrupting pathology, existing segmentation methods often fail. Here, we present a solution for the segmentation of retinal layers in dry AMD subjects by extending our previously presented loosely coupled level sets framework which operates on attenuation coefficients. In eyes affected by AMD, Bruch’s membrane becomes visible only below the drusen and our segmentation framework is adapted to delineate such a partially discernible interface. Furthermore, the initialization stage, which tentatively segments five interfaces, is modified to accommodate the appearance of drusen. This stage is based on Dijkstra's algorithm and combines prior knowledge on the shape of the interface, gradient and attenuation coefficient in the newly proposed cost function. This prior knowledge is incorporated by varying the weights for horizontal, diagonal and vertical edges. Finally, quantitative evaluation of the accuracy shows a good agreement between manual and automated segmentation.

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