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Detection of the Tear Meniscus Shape Using Asymmetric Graph-Cuts

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dc.contributor.authorYedidya, Tamir
dc.contributor.authorHartley, Richard
dc.contributor.authorGuillon, Jean-Pierre
dc.contributor.authorKanagasingam, Yogesan
dc.coverage.spatialRotterdam The Netherlands
dc.date.accessioned2015-12-10T22:57:02Z
dc.date.createdApril 14-17 2010
dc.date.issued2010
dc.date.updated2016-02-24T11:01:46Z
dc.description.abstractWe 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.
dc.identifier.urihttp://hdl.handle.net/1885/60483
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesIEEE International Symposium on Biomedical Imaging (ISBI 2010)
dc.sourceProceedings of IEEE International Symposium on Biomedical Imaging (ISBI 2010)
dc.subjectKeywords: Automatic algorithms; Dry eye; Eye images; Global properties; Meniscus shape; Shape priors; Medical imaging Asymmetry; Dry eye; Graph-cuts; Segmentation; Tear meniscus
dc.titleDetection of the Tear Meniscus Shape Using Asymmetric Graph-Cuts
dc.typeConference paper
local.bibliographicCitation.lastpage947
local.bibliographicCitation.startpage944
local.contributor.affiliationYedidya, Tamir, College of Engineering and Computer Science, ANU
local.contributor.affiliationHartley, Richard, College of Engineering and Computer Science, ANU
local.contributor.affiliationGuillon, Jean-Pierre, Lions Eye Institute
local.contributor.affiliationKanagasingam, Yogesan, Lions Eye Institute
local.contributor.authoruidYedidya, Tamir, u4187353
local.contributor.authoruidHartley, Richard, u4022238
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080104 - Computer Vision
local.identifier.absfor090399 - Biomedical Engineering not elsewhere classified
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
local.identifier.ariespublicationu4334215xPUB542
local.identifier.doi10.1109/ISBI.2010.5490143
local.identifier.scopusID2-s2.0-77955185172
local.type.statusPublished Version

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