DocumentCode :
2720065
Title :
Detection of the tear meniscus shape using asymmetric graph-cuts
Author :
Yedidya, Tamir ; Hartley, Richard ; Guillon, Jean-Pierre ; Kanagasingam, Yogesan
fYear :
2010
fDate :
14-17 April 2010
Firstpage :
944
Lastpage :
947
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.
Keywords :
bio-optics; biomedical optical imaging; eye; fluorescence; image segmentation; medical image processing; shape recognition; conjunctival folds; corneal areas; cost function; eyelids; fluorescein; global properties; graph-cuts; segmentation; slit-lamp; tear meniscus regularity; tear meniscus shape detection; Australia; Cost function; Eyelids; Eyes; Gold; Image segmentation; Pattern analysis; Reservoirs; Shape; Testing; Asymmetry; Dry Eye; Graph-Cuts; Segmentation; Tear meniscus;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
ISSN :
1945-7928
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2010.5490143
Filename :
5490143
Link To Document :
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