Browsing by Author "Saalfeld, Sylvia"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Evolutionary Pathlines for Blood Flow Exploration in Cerebral Aneurysms
    (The Eurographics Association, 2019) Behrendt, Benjamin; Engelke, Wito; Berg, Philipp; Beuing, Oliver; Preim, Bernhard; Hotz, Ingrid; Saalfeld, Sylvia; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Blood flow simulations play an important role for the understanding of vascular diseases, such as aneurysms. However, analysis of the resulting flow patterns, especially comparisons across patient groups, are challenging. Typically, the hemodynamic analysis relies on trial and error inspection of the flow data based on pathline visualizations and surface renderings. Visualizing too many pathlines at once may obstruct interesting features, e.g., embedded vortices, whereas with too little pathlines, particularities such as flow characteristics in aneurysm blebs might be missed. While filtering and clustering techniques support this task, they require the pre-computation of pathlines densely sampled in the space-time domain. Not only does this become prohibitively expensive for large patient groups, but the results often suffer from undersampling artifacts. In this work, we propose the usage of evolutionary algorithms to reduce the overhead of computing pathlines that do not contribute to the analysis, while simultaneously reducing the undersampling artifacts. Integrated in an interactive framework, it efficiently supports the evaluation of hemodynamics for clinical research and treatment planning in case of cerebral aneurysms. The specification of general optimization criteria for entire patient groups allows the blood flow data to be batch-processed. We present clinical cases to demonstrate the benefits of our approach especially in presence of aneurysm blebs. Furthermore, we conducted an evaluation with four expert neuroradiologists. As a result, we report advantages of our method for treatment planning to underpin its clinical potential.
  • Thumbnail Image
    Item
    The Virtual Reality Flow Lens for Blood Flow Exploration
    (The Eurographics Association, 2020) Behrendt, Benjamin; Piotrowski, Lisa; Saalfeld, Sylvia; Preim, Bernhard; Saalfeld, Patrick; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
    The exploration of time-dependent measured or simulated blood flow is challenging due to the complex three-dimensional structure of vessels and blood flow patterns. Especially on a 2D screen, understanding their full shape and interacting with them is difficult. Critical regions do not always stand out in the visualization and may easily be missed without proper interaction and filtering techniques. The FlowLens [GNBP11] was introduced as a focus-and-context technique to explore one specific blood flow parameter in the context of other parameters for the purpose of treatment planning. With the recent availability of affordable VR glasses it is possible to adapt the concepts of the FlowLens into immersive VR and make them available to a broader group of users. Translating the concept of the Flow Lens to VR leads to a number of design decisions not only based around what functions to include, but also how they can be made available to the user. In this paper, we present a configurable focus-and-context visualization for the use with virtual reality headsets and controllers that allows users to freely explore blood flow data within a VR environment. The advantage of such a solution is the improved perception of the complex spatial structures that results from being surrounded by them instead of observing through a small screen.
  • Thumbnail Image
    Item
    Visual Exploration of Intracranial Aneurysm Blood Flow Adapted to the Clinical Researcher
    (The Eurographics Association, 2021) Behrendt, Benjamin; Engelke, Wito; Berg, Philipp; Beuing, Oliver; Hotz, Ingrid; Preim, Bernhard; Saalfeld, Sylvia; Oeltze-Jafra, Steffen and Raidou, Renata Georgia
    Rupture risk assessment is a key to devise patient-specific treatment plans of cerebral aneurysms. To understand and predict the development of aneurysms and other vascular diseases over time, both hemodynamic flow patterns and their effect on the vessel surface need to be analyzed. Flow structures close to the vessel wall often correlate directly with local changes in surface parameters, such as pressure or wall shear stress. However, especially for the identification of specific blood flow characteristics that cause local startling parameters on the vessel surface, like elevated pressure values, an interactive analysis tool is missing. In order to find meaningful structures in the entirety of the flow, the data has to be filtered based on the respective explorative aim. Thus, we present a combination of visualization, filtering and interaction techniques for explorative analysis of blood flow with a focus on the relation of local surface parameters and underlying flow structures. In combination with a filtering-based approach, we propose the usage of evolutionary algorithms to reduce the overhead of computing pathlines that do not contribute to the analysis, while simultaneously reducing the undersampling artifacts. We present clinical cases to demonstrate the benefits of both our filter-based and evolutionary approach and showcase its potential for patient-specific treatment plans.