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dc.contributor.authorSugathan, Sherin
dc.contributor.authorBartsch, Hauke
dc.contributor.authorRiemer, Frank
dc.contributor.authorGrüner, Eli Renate
dc.contributor.authorLawonn, Kai
dc.contributor.authorSmit, Noeska Natasja
dc.description.abstractIn multiple sclerosis (MS), the amount of brain damage, anatomical location, shape, and changes are important aspects that help medical researchers and clinicians to understand the temporal patterns of the disease. Interactive visualization for longitudinal MS data can support studies aimed at exploratory analysis of lesion and healthy tissue topology. Existing visualizations in this context comprise bar charts and summary measures, such as absolute numbers and volumes to summarize lesion trajectories over time, as well as summary measures such as volume changes. These techniques can work well for datasets having dual time point comparisons. For frequent follow-up scans, understanding patterns from multimodal data is difficult without suitable visualization approaches. As a solution, we propose a visualization application, wherein we present lesion exploration tools through interactive visualizations that are suitable for large time-series data. In addition to various volumetric and temporal exploration facilities, we include an interactive stacked area graph with other integrated features that enable comparison of lesion features, such as intensity or volume change. We derive the input data for the longitudinal visualizations from automated lesion tracking. For cases with a larger number of follow-ups, our visualization design can provide useful summary information while allowing medical researchers and clinicians to study features at lower granularities. We demonstrate the utility of our visualization on simulated datasets through an evaluation with domain experts.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleLongitudinal visualization for exploratory analysis of multiple sclerosis lesionsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.source.journalComputers & graphicsen_US
dc.identifier.citationComputers & graphics. 2022, 107, 208-2019.en_US

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal