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dc.contributor.authorHong, Qingqizh_CN
dc.contributor.authorWang, Beizhanzh_CN
dc.contributor.author王备战zh_CN
dc.date.accessioned2015-07-22T02:16:11Z
dc.date.available2015-07-22T02:16:11Z
dc.date.issued2013zh_CN
dc.identifier.citationProceedings of the 2013 6th International Congress on Image and Signal Processing, CISP 2013, 2013,2:631-635zh_CN
dc.identifier.other20141117463750zh_CN
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/85744
dc.descriptionConference Name:2013 6th International Congress on Image and Signal Processing, CISP 2013. Conference Address: Hangzhou, China. Time:December 16, 2013 - December 18, 2013.zh_CN
dc.description.abstractIn this paper, a localized hybrid level-set method for vessel image segmentation is proposed. The proposed method integrates both local region information and boundary information for vessel segmentation, which is essential for the accurate extraction of tiny vessel structures. In our proposed technique, the local intensity information is firstly embedded into a region-based contour model, and then incorporated into the level-set formulation of the geodesic active contour model. Compared with the global threshold based method, the use of locally specified dynamic thresholds enables the extraction of the local image information, which is essential for the segmentation of vessel images. Experimental results on vessel images are presented to demonstrate the strengths of our localized hybrid level-set method. ? 2013 IEEE.zh_CN
dc.language.isoen_USzh_CN
dc.publisherIEEE Computer Societyzh_CN
dc.source.urihttp://dx.doi.org/10.1109/CISP.2013.6745243zh_CN
dc.subjectExtractionzh_CN
dc.subjectSignal processingzh_CN
dc.titleSegmentation of vessel images using a localized hybrid level-set methodzh_CN
dc.typeConferencezh_CN


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