Detection of the Tear Meniscus Shape Using Asymmetric Graph-Cuts
Date
2010
Authors
Yedidya, Tamir
Hartley, Richard
Guillon, Jean-Pierre
Kanagasingam, Yogesan
Journal Title
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Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
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.
Description
Keywords
Keywords: Automatic algorithms; Dry eye; Eye images; Global properties; Meniscus shape; Shape priors; Medical imaging Asymmetry; Dry eye; Graph-cuts; Segmentation; Tear meniscus
Citation
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Source
Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI 2010)
Type
Conference paper
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Restricted until
2037-12-31