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Coherence Maps for Blood Flow Exploration
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. (Vetenskaplig Visualisering)ORCID iD: 0000-0002-5693-2830
Visual Computing Group, Ulm University, Germany. (Visual Computing Research Group)
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. (Vetenskaplig Visualisering)ORCID iD: 0000-0001-7285-0483
2016 (English)In: VCBM 16: Eurographics Workshop on Visual Computing for Biology and Medicine, Eurographics - European Association for Computer Graphics, 2016, 79-88 p.Conference paper (Refereed)
Abstract [en]

Blood flow data from direct measurements (4D flow MRI) or numerical simulations opens new possibilities for the understanding of the development of cardiac diseases. However, before this new data can be used in clinical studies or for diagnosis, it is important to develop a notion of the characteristics of typical flow structures. To support this process we developed a novel blood flow clustering and exploration method. The method builds on the concept of coherent flow structures. Coherence maps for cross-sectional slices are defined to show the overall degree of coherence of the flow. In coherent regions the method summarizes the dominant blood flow using a small number of pathline representatives. In contrast to other clustering approaches the clustering is restricted to coherent regions and pathlines with low coherence values, which are not suitable for clustering and thus are not forced into clusters. The coherence map is based on the Finite-time Lyapunov Exponent (FTLE). It is created on selected planes in the inflow respective outflow area of a region of interest. The FTLE value measures the rate of separation of pathlines originating from this plane. Different to previous work using FTLE we do not focus on separating extremal lines but on local minima and regions of low FTLE intensities to extract coherent flow. The coherence map and the extracted clusters serve as basis for the flow exploration. The extracted clusters can be selected and inspected individually. Their flow rate and coherence provide a measure for their significance. Switching off clusters reduces the amount of occlusion and reveals the remaining part of the flow. The non-coherent regions can also be explored by interactive manual pathline seeding in the coherence map.

Place, publisher, year, edition, pages
Eurographics - European Association for Computer Graphics, 2016. 79-88 p.
Series
, Eurographics Workshop on Visual Computing for Biology and Medicine, ISSN 2070-5778 (print), 2070-5786 (online)
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-130979DOI: 10.2312/vcbm.20161274ISBN: 978-3-03868-010-9OAI: oai:DiVA.org:liu-130979DiVA: diva2:957464
Conference
The 6th Eurographics Workshop on Visual Computing for Biology and Medicine, Bergen, Norway, September 7-9, 2016
Available from: 2016-09-02 Created: 2016-09-02 Last updated: 2016-09-16Bibliographically approved

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Englund, RickardRopinski, TimoHotz, Ingrid
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