Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/14149
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dc.contributor.authorSalazar-Gonzalez, AG-
dc.contributor.authorLi, Y-
dc.contributor.authorLiu, X-
dc.date.accessioned2017-03-01T09:21:09Z-
dc.date.available2011-08-17-
dc.date.available2017-03-01T09:21:09Z-
dc.date.issued2011-
dc.identifier.citationIEEE SSCI 2011 - Symposium Series on Computational Intelligence - CIMI 2011: 2011 IEEE 3rd International Workshop on Computational Intelligence in Medical Imaging, 2011, pp. 1 - 8en_US
dc.identifier.isbn9781612843360-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/14149-
dc.description.abstractGlaucoma is one of the main causes of blindness worldwide. Segmentation of vascular system and optic disc is an important step in the development of an automatic retinal screening system. In this paper we present an unsupervised method for the optic disc segmentation. The main obstruction in the optic disc segmentation process is the presence of blood vessels breaking the continuity of the object. While many other methods have addressed this problem trying to eliminate the vessels, we have incorporated the blood vessel information into our formulation. The blood vessel inside of the optic disc are used to give continuity to the object to segment. Our approach is based on the graph cut technique, where the graph is constructed considering the relationship between neighboring pixels and by the likelihood of them belonging to the foreground and background from prior information. Our method was tested on two public datasets, DIARETDB1 and DRIVE. The performance of our method was measured by calculating the overlapping ratio (Oratio), sensitivity and the mean absolute distance (MAD) with respect to the manually labeled images. Experimental results demonstrate that our method outperforms other methods on these datasets. © 2011 IEEE.en_US
dc.format.extent1 - 8-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectRetinal imagesen_US
dc.subjectvessel segmentation,en_US
dc.subjectoptic disc segmentationen_US
dc.subjectgraph cut techniqueen_US
dc.titleOptic disc segmentation by incorporating blood vessel compensationen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1109/CIMI.2011.5952040-
dc.relation.isPartOfIEEE SSCI 2011 - Symposium Series on Computational Intelligence - CIMI 2011: 2011 IEEE 3rd International Workshop on Computational Intelligence in Medical Imaging-
pubs.publication-statusPublished-
Appears in Collections:Computer Science

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