Detection of the tear meniscus shape using asymmetric graph-cuts

Authors:
Tamir Yedidya;Richard Hartley;Jean-Pierre Guillon;Yogesan Kanagasingam
Affiliations:
The Australian National University and NICTA;The Australian National University and NICTA;Lions Eye Institute;Lions Eye Institute
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

We present a new fully automatic algorithm to evaluate the shape and regularity of the tear meniscus in eye images taken using a slit-lamp after instilling fluorescein. Our method analyzes the meniscus in the corneal and conjunctival areas and detects abnormalities such as conjunctival folds. We use graph-cuts to minimize a cost function to simultaneously produce a segmentation of the meniscus and the best shape prior for the eyelids. The pairwise term is asymmetric in order to capture the global properties of the meniscus and add a sense of direction. We tested our method on 43 images and provide a grading of the quality of the meniscus.