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dc.contributor.authorZhang, Guohaoen_US
dc.contributor.authorKochunov, Peteren_US
dc.contributor.authorHong, Ellioten_US
dc.contributor.authorCarr, Hamishen_US
dc.contributor.authorChen, Jianen_US
dc.contributor.editorEnrico Bertini and Niklas Elmqvist and Thomas Wischgollen_US
dc.date.accessioned2016-06-09T09:42:26Z
dc.date.available2016-06-09T09:42:26Z
dc.date.issued2016en_US
dc.identifier.isbn978-3-03868-014-7en_US
dc.identifier.issn-en_US
dc.identifier.urihttp://dx.doi.org/10.2312/eurovisshort.20161161en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.description.abstractWe present a visualization prototype for comparative analysis of factional anisotropy (FA) distributions constructed from threedimensional (3D) brain diffusion tensor imaging (DTI) in brain cohorts. The prototype lets brain scientists examine metaanalysis (the pooled analysis of multiple smaller trials or multi-site studies) results for identifying differences in cohorts. Interactive side-by-side bar charts show multiple statistical results of FA comparisons in regions of interest (ROIs) defined by user-chosen atlas. An occlusion-free two-dimensional (2D) semantic merge tree further displays the global distribution of FA values. Two histograms on each tree arc reveal voxel-based FA distributions represented by that arc branch in cohorts. Interaction techniques support brushing-and-linking of local and global ROIs queries. ROIs can be defined from atlas or select through interaction. We report validation results in a case study and an interview.en_US
dc.publisherThe Eurographics Associationen_US
dc.titleTowards Visual Mega-Analysis of Voxel-based Measurement in Brain Cohortsen_US
dc.description.seriesinformationEuroVis 2016 - Short Papersen_US
dc.description.sectionheadersMedical Visualizationen_US
dc.identifier.doi10.2312/eurovisshort.20161161en_US
dc.identifier.pages55-59en_US


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