dc.contributor.author | Apilla, Vikram | en_US |
dc.contributor.author | Behrendt, Benjamin | en_US |
dc.contributor.author | Lawonn, Kai | en_US |
dc.contributor.author | Preim, Bernhard | en_US |
dc.contributor.author | Meuschke, Monique | en_US |
dc.contributor.editor | Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas | en_US |
dc.date.accessioned | 2021-09-21T08:09:44Z | |
dc.date.available | 2021-09-21T08:09:44Z | |
dc.date.issued | 2021 | |
dc.identifier.isbn | 978-3-03868-140-3 | |
dc.identifier.issn | 2070-5786 | |
dc.identifier.uri | https://doi.org/10.2312/vcbm.20211349 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/vcbm20211349 | |
dc.description.abstract | We present an approach for computing camera animations composed of optimal views to support the visual exploration of blood flow data using cerebral aneurysms as major example. Medical researchers are interested in hemodynamic parameters and vessel wall characteristics. The time-dependent character of blood flow data complicates the visual analysis. Our approach is modeled as an optimization problem to automatically determine camera paths during the cardiac cycle. These consist of optimal viewpoints showing regions with suspicious characteristics of wall- and flow-related parameters. This provides medical researchers with an efficient method of obtaining a fast overview of patient-specific blood flow data. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Applied computing | |
dc.subject | Life and medical sciences | |
dc.subject | Human centered computing | |
dc.subject | Visualization | |
dc.title | Automatic Animations to Analyze Blood Flow Data | en_US |
dc.description.seriesinformation | Eurographics Workshop on Visual Computing for Biology and Medicine | |
dc.description.sectionheaders | The path that blood takes | |
dc.identifier.doi | 10.2312/vcbm.20211349 | |
dc.identifier.pages | 101-105 | |