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dc.contributor.authorGuo, Yishien_US
dc.contributor.authorWang, Yangen_US
dc.contributor.authorFang, Shiaofenen_US
dc.contributor.authorChao, Hongyangen_US
dc.contributor.authorSaykin, Andrewen_US
dc.contributor.authorShen, Lien_US
dc.contributor.editorMiriah Meyer and Tino Weinkaufsen_US
dc.date.accessioned2013-11-08T10:22:36Z
dc.date.available2013-11-08T10:22:36Z
dc.date.issued2012en_US
dc.identifier.isbn978-3-905673-91-3en_US
dc.identifier.urihttp://dx.doi.org/10.2312/PE/EuroVisShort/EuroVisShort2012/078-083en_US
dc.description.abstractThe human brain is a complex network with countless connected neurons, and can be described as a "connectome". Existing studies on analyzing human connectome data are primarily focused on characterizing the brain networks with a small number of easily computable measures that may be inadequate for revealing complex relationship between brain function and its structural substrate. To facilitate large-scale connectomic analysis, in this paper, we propose a powerful and flexible volume rendering scheme to effectively visualize and interactively explore thousands of network measures in the context of brain anatomy, and to aid pattern discovery.We demonstrate the effectiveness of the proposed scheme by applying it to a real connectome data set.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.8 [Computer Graphics]: Applicationsen_US
dc.titlePattern Visualization of Human Connectome Dataen_US
dc.description.seriesinformationEuroVis - Short Papersen_US


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