Browsing by Author "Hotz, Ingrid"

Now showing 1 - 9 of 9
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    Autonomous Particles for Interactive Flow Visualization
    (© 2019 The Eurographics Association and John Wiley & Sons Ltd., 2019) Engelke, Wito; Lawonn, Kai; Preim, Bernhard; Hotz, Ingrid; Chen, Min and Benes, Bedrich
    We present an interactive approach to analyse flow fields using a new type of particle system, which is composed of autonomous particles exploring the flow. While particles provide a very intuitive way to visualize flows, it is a challenge to capture the important features with such systems. Particles tend to cluster in regions of low velocity and regions of interest are often sparsely populated. To overcome these disadvantages, we propose an automatic adaption of the particle density with respect to local importance measures. These measures are user defined and the systems sensitivity to them can be adjusted interactively. Together with the particle history, these measures define a probability for particles to multiply or die, respectively. There is no communication between the particles and no neighbourhood information has to be maintained. Thus, the particles can be handled in parallel and support a real‐time investigation of flow fields. To enhance the visualization, the particles' properties and selected field measures are also used to specify the systems rendering parameters, such as colour and size. We demonstrate the effectiveness of our approach on different simulated vector fields from technical and medical applications.We present an interactive approach to analyse flow fields using a new type of particle system, which is composed of autonomous particles exploring the flow. While particles provide a very intuitive way to visualize flows, it is a challenge to capture the important features with such systems. Particles tend to cluster in regions of low velocity and regions of interest are often sparsely populated. To overcome these disadvantages, we propose an automatic adaption of the particle density with respect to local importance measures. These measures are user defined and the systems sensitivity to them can be adjusted interactively. Together with the particle history, these measures define a probability for particles to multiply or die, respectively. There is no communication between the particles and no neighbourhood information has to be maintained. Thus, the particles can be handled in parallel and support a real‐time investigation of flow fields. To enhance the visualization, the particles' properties and selected field measures are also used to specify the systems rendering parameters, such as colour and size. We demonstrate the effectiveness of our approach on different simulated vector fields from technical and medical applications.
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    Eurographics Workshop on Visual Computing for Biology and Medicine 2017: Frontmatter
    (Eurographics Association, 2017) Bruckner, Stefan; Hennemuth, Anja; Kainz, Bernhard; Hotz, Ingrid; Merhof, Dorit; Rieder, Christian; Stefan Bruckner and Anja Hennemuth and Bernhard Kainz and Ingrid Hotz and Dorit Merhof and Christian Rieder
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    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.
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    Frontmatter: Eurographics Workshop on Visual Computing for Biology and Medicine 2018
    (The Eurographics Association, 2018) Puig Puig, Anna; Schultz, Thomas; Vilanova, Anna; Hotz, Ingrid; Kozlikova, Barbora; Vázquez, Pere-Pau; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
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    MolFind - Integrated Multi-Selection Schemes for Complex Molecular Structures
    (The Eurographics Association, 2019) Skånberg, Robin; Linares, Mathieu; Falk, Martin; Hotz, Ingrid; Ynnerman, Anders; Byska, Jan and Krone, Michael and Sommer, Björn
    Selecting components and observing changes of properties and configurations over time is an important step in the analysis of molecular dynamics (MD) data. In this paper, we present a selection tool combining text-based queries with spatial selection and filtering. Morphological operations facilitate refinement of the selection by growth operators, e.g. across covalent bonds. The combination of different selection paradigms enables flexible and intuitive analysis on different levels of detail and visual depiction of molecular events. Immediate visual feedback during interactions ensures a smooth exploration of the data. We demonstrate the utility of our selection framework by analyzing temporal changes in the secondary structure of poly-alanine and the binding of aspirin to phospholipase A2.
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    State of the Art in Time-Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Bujack, Roxana; Yan, Lin; Hotz, Ingrid; Garth, Christoph; Wang, Bei; Smit, Noeska and Oeltze-Jafra, Steffen and Wang, Bei
    We present a state-of-the-art report on time-dependent flow topology. We survey representative papers in visualization and provide a taxonomy of existing approaches that generalize flow topology from time-independent to time-dependent settings. The approaches are classified based upon four categories: tracking of steady topology, reference frame adaption, pathline classification or clustering, and generalization of critical points. Our unique contributions include introducing a set of desirable mathematical properties to interpret physical meaningfulness for time-dependent flow visualization, inferring mathematical properties associated with selective research papers, and utilizing such properties for classification. The five most important properties identified in the existing literature include coincidence with the steady case, induction of a partition within the domain, Lagrangian invariance, objectivity, and Galilean invariance.
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    Visual Analysis of Electronic Densities and Transitions in Molecules
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Masood, Talha Bin; Thygesen, Signe Sidwall; Linares, Mathieu; Abrikosov, Alexei I.; Natarajan, Vijay; Hotz, Ingrid; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    The study of electronic transitions within a molecule connected to the absorption or emission of light is a common task in the process of the design of new materials. The transitions are complex quantum mechanical processes and a detailed analysis requires a breakdown of these processes into components that can be interpreted via characteristic chemical properties. We approach these tasks by providing a detailed analysis of the electron density field. This entails methods to quantify and visualize electron localization and transfer from molecular subgroups combining spatial and abstract representations. The core of our method uses geometric segmentation of the electronic density field coupled with a graph-theoretic formulation of charge transfer between molecular subgroups. The design of the methods has been guided by the goal of providing a generic and objective analysis following fundamental concepts. We illustrate the proposed approach using several case studies involving the study of electronic transitions in different molecular systems.
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    A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data
    (The Eurographics Association, 2019) Jönsson, Daniel; Bergström, Albin; Forsell, Camilla; Simon, Rozalyn; Engström, Maria; Ynnerman, Anders; Hotz, Ingrid; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    We present an interactive visual environment for linked analysis of brain imaging and clinical measurements. The environment is developed in an iterative participatory design process involving neuroscientists investigating the causes of brain-related complex diseases. The hypotheses formation process about correlations between active brain regions and physiological or psychological factors in studies with hundreds of subjects is a central part of the investigation. Observing the reasoning patterns during hypotheses formation, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration, thus limiting the scientific scope and preventing extraction of knowledge from available data. Based on these observations, we designed methods that support neuroscientists by integrating their existing statistical analysis of multivariate subject data with interactive visual exploration to enable them to better understand differences between patient groups and the complex bidirectional interplay between clinical measurement and the brain. These exploration concepts enable neuroscientists, for the first time during their investigations, to interactively move between and reason about questions such as 'which clinical measurements are correlated with a specific brain region?' or 'are there differences in brain activity between depressed young and old subjects?'. The environment uses parallel coordinates for effective overview and selection of subject groups, Welch's t-test to filter out brain regions with statistically significant differences, and multiple visualizations of Pearson correlations between brain regions and clinical parameters to facilitate correlation analysis. A qualitative user study was performed with three neuroscientists from different domains. The study shows that the developed environment supports simultaneous analysis of more parameters, provides rapid pathways to insights, and is an effective support tool for hypothesis formation.
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    A Winding Angle Framework for Tracking and Exploring Eddy Transport in Oceanic Ensemble Simulations
    (The Eurographics Association, 2021) Friederici, Anke; Falk, Martin; Hotz, Ingrid; Dutta, Soumya and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirk
    Oceanic eddies, which are highly mass-coherent vortices traveling through the earth's waters, are of special interest for their mixing properties. Therefore, large-scale ensemble simulations are performed to approximate their possible evolution. Analyzing their development and transport behavior requires a stable extraction of both their shape and properties of water masses within. We present a framework for extracting the time series of full 3D eddy geometries based on an winding angle criterion. Our analysis tools enables users to explore the results in-depth by linking extracted volumes to extensive statistics collected across several ensemble members. The methods are showcased on an ensemble simulation of the Red Sea. We show that our extraction produces stable and coherent geometries even for highly irregular eddies in the Red Sea. These capabilities are utilized to evaluate the stability of our method with respect to variations of user-defined parameters. Feedback gathered from domain experts was very positive and indicates that our methods will be considered for newly simulated, even larger data sets.