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dc.contributor.authorChen, CMen_US
dc.contributor.authorLu, HHSen_US
dc.contributor.authorHuang, YSen_US
dc.date.accessioned2014-12-08T15:42:07Z-
dc.date.available2014-12-08T15:42:07Z-
dc.date.issued2002-08-01en_US
dc.identifier.issn0301-5629en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0301-5629(02)00531-8en_US
dc.identifier.urihttp://hdl.handle.net/11536/28615-
dc.description.abstractTwo common deficiencies of most conventional deformable models are the need to place the initial contour very close to the desired boundary and the incapability of capturing a highly winding boundary for sonographic boundary extraction. To remedy these two deficiencies, a new deformable model (namely, the cell-based dual snake model) is proposed in this paper. The basic idea is to apply the dual snake model in the cell-based deformation manner. While the dual snake model provides an effective mechanism allowing a distant initial contour, the cell-based deformation makes it possible to catch the winding characteristics of the desired boundary. The performance of the proposed cell-based dual snake model has been evaluated on synthetic images with simulated speckles and on the clinical ultrasound (US) images. The experimental results show that the mean distances from the derived to the desired boundary points are 0.9 +/- 0.42 pixels and 1.29 +/- 0.39 pixels for the synthetic and the clinical US images, respectively.en_US
dc.language.isoen_USen_US
dc.subjectboundary extractionen_US
dc.subjectultrasound imagesen_US
dc.subjectdeformable modelen_US
dc.subjectdual snake modelen_US
dc.subjectcell-based deformationen_US
dc.subjectwatershed transformen_US
dc.subjectmultiscale Gaussian filtersen_US
dc.titleCell-based dual snake model: A new approach to extracting highly winding boundaries in the ultrasound imagesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0301-5629(02)00531-8en_US
dc.identifier.journalULTRASOUND IN MEDICINE AND BIOLOGYen_US
dc.citation.volume28en_US
dc.citation.issue8en_US
dc.citation.spage1061en_US
dc.citation.epage1073en_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.identifier.wosnumberWOS:000177916300010-
dc.citation.woscount12-
Appears in Collections:Articles