Transdisciplinary Visualization of Aortic Dissections

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dc.contributor.authorMistelbauer, Gabrielen_US
dc.contributor.authorBäumler, Kathrinen_US
dc.contributor.authorMastrodicasa, Domenicoen_US
dc.contributor.authorHahn, Lewis D.en_US
dc.contributor.authorPepe, Antonioen_US
dc.contributor.authorSandfort, Veiten_US
dc.contributor.authorHinostroza, Virginiaen_US
dc.contributor.authorOstendorf, Kaien_US
dc.contributor.authorSchroeder, Aaronen_US
dc.contributor.authorSailer, Anna M.en_US
dc.contributor.authorWillemink, Martin J.en_US
dc.contributor.authorWalters, Shannonen_US
dc.contributor.authorPreim, Bernharden_US
dc.contributor.authorFleischmann, Dominiken_US
dc.contributor.editorRaidou, Renataen_US
dc.contributor.editorKuhlen, Torstenen_US
dc.date.accessioned2023-06-12T04:48:01Z
dc.date.available2023-06-12T04:48:01Z
dc.date.issued2023
dc.description.abstractAortic dissection is a life-threatening condition caused by the abrupt formation of a secondary blood flow channel within the vessel wall. Patients surviving the acute phase remain at high risk for late complications, such as aneurysm formation and aortic rupture. The timing of these complications is variable, making long-term imaging surveillance crucial for aortic growth monitoring. Morphological characteristics of the aorta, its hemodynamics, and, ultimately, risk models impact treatment strategies. Providing such a wealth of information demands expertise across a broad spectrum to understand the complex interplay of these influencing factors. We present results of our longstanding transdisciplinary efforts to confront this challenge. Our team has identified four key disciplines, each requiring specific expertise overseen by radiology: lumen segmentation and landmark detection, risk predictors and inter-observer analysis, computational fluid dynamics simulations, and visualization and modeling. In each of these disciplines, visualization supports analysis and serves as communication medium between stakeholders, including patients. For each discipline, we summarize the work performed, the related work, and the results.en_US
dc.description.sectionheaders3rd Prize
dc.description.seriesinformationEuroVis 2023 - Dirk Bartz Prize
dc.identifier.doi10.2312/evm.20231085
dc.identifier.isbn978-3-03868-221-9
dc.identifier.pages1-5
dc.identifier.pages5 pages
dc.identifier.urihttps://doi.org/10.2312/evm.20231085
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evm20231085
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Applied computing -> Life and medical sciences; Human-centered computing -> Visualization; Computing methodologies -> Computer graphics; Modeling and simulation; Machine learning
dc.subjectApplied computing
dc.subjectLife and medical sciences
dc.subjectHuman centered computing
dc.subjectVisualization
dc.subjectComputing methodologies
dc.subjectComputer graphics
dc.subjectModeling and simulation
dc.subjectMachine learning
dc.titleTransdisciplinary Visualization of Aortic Dissectionsen_US
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