Browsing by Author "Hotz, Ingrid"

Now showing 1 - 5 of 5
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    Level of Detail Exploration of Electronic Transition Ensembles using Hierarchical Clustering
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Sidwall Thygesen, Signe; Masood, Talha Bin; Linares, Mathieu; Natarajan, Vijay; Hotz, Ingrid; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    We present a pipeline for the interactive visual analysis and exploration of molecular electronic transition ensembles. Each ensemble member is specified by a molecular configuration, the charge transfer between two molecular states, and a set of physical properties. The pipeline is targeted towards theoretical chemists, supporting them in comparing and characterizing electronic transitions by combining automatic and interactive visual analysis. A quantitative feature vector characterizing the electron charge transfer serves as the basis for hierarchical clustering as well as for the visual representations. The interface for the visual exploration consists of four components. A dendrogram provides an overview of the ensemble. It is augmented with a level of detail glyph for each cluster. A scatterplot using dimensionality reduction provides a second visualization, highlighting ensemble outliers. Parallel coordinates show the correlation with physical parameters. A spatial representation of selected ensemble members supports an in-depth inspection of transitions in a form that is familiar to chemists. All views are linked and can be used to filter and select ensemble members. The usefulness of the pipeline is shown in three different case studies.
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    Level of Detail Visual Analysis of Structures in Solid-State Materials
    (The Eurographics Association, 2023) Thygesen, Signe Sidwall; Abrikosov, Alexei I.; Steneteg, Peter; Masood, Talha Bin; Hotz, Ingrid; Hoellt, Thomas; Aigner, Wolfgang; Wang, Bei
    We propose a visual analysis method for the comparison and evaluation of structures in solid-state materials based on the electron density field using topological analysis. The work has been motivated by a material science application, specifically looking for new so-called layered materials whose physical properties are required in many modern technological developments. Due to the incredibly large search space, this is a slow and tedious process, requiring efficient data analysis to characterize and understand the material properties. The core of our proposed analysis pipeline is an abstract bar representation that serves as a concise signature of the material, supporting direct comparison and also an exploration of different material candidates.
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    Visual Analysis of Charge Flow Networks for Complex Morphologies
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Kottravel, Sathish; Falk, Martin; Bin Masood, Talha; linares, mathieu; Hotz, Ingrid; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    In the field of organic electronics, understanding complex material morphologies and their role in efficient charge transport in solar cells is extremely important. Related processes are studied using the Ising model and Kinetic Monte Carlo simulations resulting in large ensembles of stochastic trajectories. Naive visualization of these trajectories, individually or as a whole, does not lead to new knowledge discovery through exploration. In this paper, we present novel visualization and exploration methods to analyze this complex dynamic data, which provide succinct and meaningful abstractions leading to scientific insights. We propose a morphology abstraction yielding a network composed of material pockets and the interfaces, which serves as backbone for the visualization of the charge diffusion. The trajectory network is created using a novel way of implicitly attracting the trajectories to the skeleton of the morphology relying on a relaxation process. Each individual trajectory is then represented as a connected sequence of nodes in the skeleton. The final network summarizes all of these sequences in a single aggregated network. We apply our method to three different morphologies and demonstrate its suitability for exploring this kind of data.
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    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.
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    VisualNeuro: A Hypothesis Formation and Reasoning Application for Multi‐Variate Brain Cohort Study Data
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Jönsson, Daniel; Bergström, Albin; Forsell, Camilla; Simon, Rozalyn; Engström, Maria; Walter, Susanna; Ynnerman, Anders; Hotz, Ingrid; Benes, Bedrich and Hauser, Helwig
    We present an application, and its development process, for interactive visual analysis of brain imaging data and clinical measurements. The application targets neuroscientists interested in understanding the correlations between active brain regions and physiological or psychological factors. The application has been developed in a participatory design process and has subsequently been released as the free software ‘VisualNeuro’. From initial observations of the neuroscientists' workflow, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration requiring the use of many tools side by side. Consequently, our application has been designed to simplify the workflow combining statistical analysis with interactive visual exploration. The resulting environment comprises parallel coordinates for effective overview and selection, Welch's t‐test to filter out brain regions with statistically significant differences and multiple visualizations for comparison between brain regions and clinical parameters. These exploration concepts enable neuroscientists to interactively explore the complex bidirectional interplay between clinical and brain measurements and easily compare different patient groups. A qualitative user study has been 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 tool for hypothesis formation.