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

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

Novosel, J. (TU Delft ImPhys/Quantitative Imaging; Rotterdam Eye Hospital)
Wang, Ziyuan
de Jong, Henk (Rotterdam Eye Hospital)
Vermeer, K.A. (Rotterdam Eye Hospital)
van Vliet, L.J. (TU Delft ImPhys/Quantitative Imaging)

Styner, Martin A. (editor)
Angelini, Elsa D. (editor)

2016

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.

Optical coherence tomography
attenuation coefficient
Dijkstra's algorithm

http://resolver.tudelft.nl/uuid:abaad308-aacd-42f3-b1e1-0944f881ff6d

https://doi.org/10.1117/12.2214698

SPIE

9781510600195

Medical Imaging 2016: Image Processing, 9784

Medical Imaging 2016: Image Processing, 2016-03-01 → 2016-03-03, San Diego, United States

Proceedings of SPIE, 9784

Institutional Repository

conference paper

© 2016 J. Novosel, Ziyuan Wang, Henk de Jong, K.A. Vermeer, L.J. van Vliet