Automated segmentation of retinal layers in OCT imaging and derived ophthalmic measures

Authors:
Florence Rossant;Itebeddine Ghorbel;Isabelle Bloch;Michel Paques;Sarah Tick
Affiliations:
ISEP Paris;ISEP Paris and Télécom ParisTech, CNRS, UMR, LTCI, Paris and FOVEA Pharmaceuticals Paris;Télécom ParisTech, CNRS, UMR, LTCI, Paris;Clinical Investigation Center, Centre Hospitalier National des Quinze-Vingts Paris;Clinical Investigation Center, Centre Hospitalier National des Quinze-Vingts Paris
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

This paper proposes an automated method for the segmentation of eight retinal layers in high resolution OCT images. It has been evaluated based on comparison with manual segmentation performed by five different experts. The method has been successfully applied on a database of 72 images. Quantitative measures are then derived as an aid to ophthalmic diagnosis. A good agreement with measures derived from manual segmentation is obtained which allows us to use the proposed method for retinal variability studies.