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dc.contributor.authorMeuschke, Moniqueen_US
dc.contributor.authorKöhler, Benen_US
dc.contributor.authorPreim, Bernharden_US
dc.contributor.authorLawonn, Kaien_US
dc.contributor.editorKai Lawonn and Mario Hlawitschka and Paul Rosenthalen_US
dc.date.accessioned2016-06-09T09:31:52Z
dc.date.available2016-06-09T09:31:52Z
dc.date.issued2016en_US
dc.identifier.isbn978-3-03868-017-8en_US
dc.identifier.issn-en_US
dc.identifier.issn1017-4656en_US
dc.identifier.urihttp://dx.doi.org/10.2312/eurorv3.20161114en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.description.abstractIn this paper, we report on our experiences that we made during our contributions in the field of the visualization of flow characteristics. Mainly, we focused on the vortex flow classification in 4D PC-MRI as current medical studies assume a strong correlation between cardiovascular diseases and blood flow patterns such as vortices. For further analysis, medical experts are asked to manually extract and classify such vortices according to specific properties. We presented and evaluated techniques that enable a fast and robust vortex classification [MLK 16,MKP 16] that supports medical experts. The main focus in this paper is a report that describes our conversations with the domain experts. The dialog was the fundament that gave us the direction of what the experts need. We derived several requirements that should be fulfilled by our tool. From this, we developed a prototype that supports the experts. Finally, we describe the evaluation of our framework and discuss currently limitations.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.9 [Computer Graphics]en_US
dc.subjectImage Processing and Computer Visionen_US
dc.subjectApplicationsen_US
dc.titleOn the Evaluation of a Semi-Automatic Vortex Flow Classification in 4D PC-MRI Data of the Aortaen_US
dc.description.seriesinformationEuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)en_US
dc.description.sectionheadersEvaluation and Validation Methods for Medical Applicationsen_US
dc.identifier.doi10.2312/eurorv3.20161114en_US
dc.identifier.pages35-39en_US


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