Compression, Segmentation, and Modeling of Filamentary Volumetric Data

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dc.contributor.authorMcCormick, B.en_US
dc.contributor.authorBusse, B.en_US
dc.contributor.authorDoddapaneni, P.en_US
dc.contributor.authorMelek, Z.en_US
dc.contributor.authorKeyser, J.en_US
dc.contributor.editorGershon Elber and Nicholas Patrikalakis and Pere Bruneten_US
dc.date.accessioned2016-02-17T18:02:47Z
dc.date.available2016-02-17T18:02:47Z
dc.date.issued2004en_US
dc.description.abstractWe present a data structure for the representation of filamentary volumetric data, called the L-block. While the L-block can be used to represent arbitrary volume data sets, it is particularly geared towards representing long, thin, branching structures that prior volumetric representations have difficulty dealing with efficiently. The data structure is designed to allow for easy compression, storage, segmentation, and reconstruction of volumetric data such as scanned neuronal data. By ''polymerizing'' adjacent connected voxels into connected components, L-block construction facilitates real-time data compression and segmentation, as well as subsequent geometric modeling and visualization of embedded objects within the volume data set. We describe its application in the context of reconstruction of brain microstructure at a neuronal level of detail.en_US
dc.description.sectionheadersPosters Sessionen_US
dc.description.seriesinformationSolid Modelingen_US
dc.identifier.doi10.2312/sm.20041411en_US
dc.identifier.isbn3-905673-55-Xen_US
dc.identifier.issn1811-7783en_US
dc.identifier.pages333-338en_US
dc.identifier.urihttps://doi.org/10.2312/sm.20041411en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.5[Computer Graphics]en_US
dc.subjectCurveen_US
dc.subjectSurfaceen_US
dc.subjectSoliden_US
dc.subjectCurve Generationen_US
dc.subjectI.4.10[Image Processing and Computer Vision]en_US
dc.subjectImage Representationen_US
dc.subjectVolumetricen_US
dc.subjectJ.3[Computer Applications]en_US
dc.subjectBiology and Geneticsen_US
dc.titleCompression, Segmentation, and Modeling of Filamentary Volumetric Dataen_US
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