Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23772
DC FieldValueLanguage
dc.contributorDepartment of Computing-
dc.creatorLi, Q-
dc.creatorYou, J-
dc.creatorZhang, L-
dc.creatorBhattacharya, P-
dc.date.accessioned2015-09-30T09:43:14Z-
dc.date.available2015-09-30T09:43:14Z-
dc.identifier.isbn1-4244-0069-4-
dc.identifier.urihttp://hdl.handle.net/10397/23772-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEyeen_US
dc.subjectImage segmentationen_US
dc.subjectMedical image processingen_US
dc.titleAutomated retinal vessel segmentation using multiscale analysis and adaptive thresholdingen_US
dc.typeConference Paperen_US
dc.identifier.spage139-
dc.identifier.epage143-
dc.identifier.doi10.1109/SSIAI.2006.1633738-
dcterms.abstractComputer based analysis for automated segmentation of blood vessels in retinal images helps eye care specialists screen larger populations for vessel abnormalities. Because the width of retinal vessels can vary from very large to very small, and the local contrast of vessels is unstable especially in unhealthy ocular fundus, the automated retinal segmentation is difficult. We propose a novel method with the consideration of these problems. Our method includes: 1) a multiscale analysis scheme using Gabor fillers and scale production, 2) an adaptive thresholding scheme using adaptive tracking and morphological filtering. Our method is good for detecting large and small vessels concurrently. It is also efficient to denoise and enhance the responses of line filters so that the vessels with low local contrast can be detected-
dcterms.bibliographicCitation2006 IEEE Southwest Symposium on Image Analysis and Interpretation, March 26-28, 2006, Denver, CO, p. 139-143-
dcterms.issued2006-
dc.relation.ispartofbook2006 IEEE Southwest Symposium on Image Analysis and Interpretation, March 26-28, 2006, Denver, CO-
dc.identifier.rosgroupidr29136-
dc.description.ros2005-2006 > Academic research: refereed > Refereed conference paper-
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