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Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5928
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dc.creatorLorigo, Liana M.-
dc.creatorFaugeras, Olivier-
dc.creatorGrimson, W.E.L.-
dc.creatorKeriven, Renaud-
dc.creatorKikinis, Ron-
dc.creatorWestin, Carl-Fredrik-
dc.date2004-10-04T14:15:21Z-
dc.date2004-10-04T14:15:21Z-
dc.date1999-08-11-
dc.date.accessioned2013-10-09T02:42:01Z-
dc.date.available2013-10-09T02:42:01Z-
dc.date.issued2013-10-09-
dc.identifierAIM-1662-
dc.identifierhttp://hdl.handle.net/1721.1/5928-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/1721-
dc.descriptionAutomatic and semi-automatic magnetic resonance angiography (MRA)s segmentation techniques can potentially save radiologists larges amounts of time required for manual segmentation and cans facilitate further data analysis. The proposed MRAs segmentation method uses a mathematical modeling technique whichs is well-suited to the complicated curve-like structure of bloods vessels. We define the segmentation task as ans energy minimization over all 3D curves and use a level set methods to search for a solution. Ours approach is an extension of previous level set segmentations techniques to higher co-dimension.-
dc.format14 p.-
dc.format6965388 bytes-
dc.format918981 bytes-
dc.formatapplication/postscript-
dc.formatapplication/pdf-
dc.languageen_US-
dc.relationAIM-1662-
dc.subjectmedical image analysis-
dc.subjectsegmentation-
dc.subjectsmagnetic resonance angiography-
dc.subjectactive contours-
dc.subjectslevel sets-
dc.titleCo-dimension 2 Geodesic Active Contours for MRA Segmentation-
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