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dc.contributor.authorBehrendt, Benjaminen_US
dc.contributor.authorEbel, Sebastianen_US
dc.contributor.authorGutberlet, Matthiasen_US
dc.contributor.authorPreim, Bernharden_US
dc.contributor.editorPuig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pauen_US
dc.date.accessioned2018-09-19T15:19:30Z
dc.date.available2018-09-19T15:19:30Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-056-7
dc.identifier.issn2070-5786
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20181236
dc.identifier.urihttps://doi.org/10.2312/vcbm.20181236
dc.description.abstractFour-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) allows for the non-invasive acquisition of in-vivo blood flow, producing a patient-specific blood flow model in selected vascular structures, e.g. the aorta. In the past, many specialized techniques for the visualization and exploration of such datasets have been developed, yet a tool for the visual comparison of multiple datasets is missing. Due to the complexity of the underlying data, a simple side-by-side comparison of two datasets using traditional visualization techniques can only yield coarse results. In this paper, we present a toolkit that allows for an efficient and robust registration of different 4D PC-MRI datasets and offers a variety of both qualitative and quantitative comparison techniques. Differences in the segmentation and time frame can be amended semi-automatically using landmarks on the vessel centerline and flow curve of the datasets. A set of measures quantifying the difference between the datasets, such as the flow jet displacement or flow angle and velocity difference, is automatically computed. To support the orientation in the spatio-temporal domain of the flow dataset, we provide bulls-eye plots that highlight potentially interesting regions. In an evaluation with three experienced radiologists, we confirmed the usefulness of our technique. With our application, they were able to discover previously unnoticed artifacts occurring in a dataset acquired with an experimental MRI sequence.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisualization toolkits
dc.subjectInformation visualization
dc.titleA Framework for Visual Comparison of 4D PC-MRI Aortic Blood Flow Dataen_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.description.sectionheadersCardiovascular
dc.identifier.doi10.2312/vcbm.20181236
dc.identifier.pages117-121


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