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dc.contributor.authorDabbaghchian, Saeeden_US
dc.contributor.editorJain, Eakta and Kosinka, Jiríen_US
dc.date.accessioned2018-04-14T18:29:56Z
dc.date.available2018-04-14T18:29:56Z
dc.date.issued2018
dc.identifier.issn1017-4656
dc.identifier.urihttp://dx.doi.org/10.2312/egp.20181018
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egp20181018
dc.description.abstractDetecting the boundaries of an enclosed region is a problem which arises in some applications such as the human upper airway modeling. Using of standard algorithms fails because of the inevitable errors, i.e. gaps and overlaps between the surrounding boundaries. Growing circles is an automatic approach to address this problem. A circle is centered inside the region and starts to grow by increasing its radius. Its growth is limited either by the surrounding boundaries or by reaching its maximum radius. To deal with complex shapes, many circles are used in which each circle partially reconstructs the region, and the whole region is determined by the union of these partial regions. The center of the circles and their maximum radius are calculated adaptively. It is similar to the region growing algorithm which is widely used in image processing applications. However, it works for unstructured grids as well as Cartesian ones. As an application of the method, it is applied to detect the boundaries of the upper airway cross-sections.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectShape modeling
dc.subjectReconstruction
dc.subjectApplied computing
dc.subjectPhysics
dc.titleGrowing Circles: A Region Growing Algorithm for Unstructured Grids and Non-aligned Boundariesen_US
dc.description.seriesinformationEG 2018 - Posters
dc.description.sectionheadersPosters
dc.identifier.doi10.2312/egp.20181018
dc.identifier.pages21-22


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