Browsing by Author "Bruckner, Stefan"

Now showing 1 - 9 of 9
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    Dynamic Visibility-Driven Molecular Surfaces
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Bruckner, Stefan; Alliez, Pierre and Pellacini, Fabio
    Molecular surface representations are an important tool for the visual analysis of molecular structure and function. In this paper, we present a novel method for the visualization of dynamic molecular surfaces based on the Gaussian model. In contrast to previous approaches, our technique does not rely on the construction of intermediate representations such as grids or triangulated surfaces. Instead, it operates entirely in image space, which enables us to exploit visibility information to efficiently skip unnecessary computations. With this visibility-driven approach, we can visualize dynamic high-quality surfaces for molecules consisting of millions of atoms. Our approach requires no preprocessing, allows for the interactive adjustment of all properties and parameters, and is significantly faster than previous approaches, while providing superior quality.
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    EuroVis 2023 CGF 42-3 STARs: Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Bruckner, Stefan; Raidou, Renata G.; Turkay, Cagatay; Bruckner, Stefan; Raidou, Renata G.; Turkay, Cagatay
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    An Exploration of Practice and Preferences for the Visual Communication of Biomedical Processes
    (The Eurographics Association, 2021) Garrison, Laura; Meuschke, Monique; Fairman, Jennifer; Smit, Noeska N.; Preim, Bernhard; Bruckner, Stefan; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    The visual communication of biomedical processes draws from diverse techniques in both visualization and biomedical illustration. However, matching these techniques to their intended audience often relies on practice-based heuristics or narrow-scope evaluations. We present an exploratory study of the criteria that audiences use when evaluating a biomedical process visualization targeted for communication. Designed over a series of expert interviews and focus groups, our study focuses on common communication scenarios of five well-known biomedical processes and their standard visual representations. We framed these scenarios in a survey with participant expertise spanning from minimal to expert knowledge of a given topic. Our results show frequent overlap in abstraction preferences between expert and non-expert audiences, with similar prioritization of clarity and the ability of an asset to meet a given communication objective. We also found that some illustrative conventions are not as clear as we thought, e.g., glows have broadly ambiguous meaning, while other approaches were unexpectedly preferred, e.g., biomedical illustrations in place of data-driven visualizations. Our findings suggest numerous opportunities for the continued convergence of visualization and biomedical illustration techniques for targeted visualization design.
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    Hornero: Thunderstorms Characterization using Visual Analytics
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Diehl, Alexandra; Pelorosso, Rodrigo; Ruiz, Juan; Pajarola, Renato; Gröller, M. Eduard; Bruckner, Stefan; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Analyzing the evolution of thunderstorms is critical in determining the potential for the development of severe weather events. Existing visualization systems for short-term weather forecasting (nowcasting) allow for basic analysis and prediction of storm developments. However, they lack advanced visual features for efficient decision-making. We developed a visual analytics tool for the detection of hazardous thunderstorms and their characterization, using a visual design centered on a reformulated expert task workflow that includes visual features to overview storms and quickly identify high-impact weather events, a novel storm graph visualization to inspect and analyze the storm structure, as well as a set of interactive views for efficient identification of similar storm cells (known as analogs) in historical data and their use for nowcasting. Our tool was designed with and evaluated by meteorologists and expert forecasters working in short-term operational weather forecasting of severe weather events. Results show that our solution suits the forecasters' workflow. Our visual design is expressive, easy to use, and effective for prompt analysis and quick decision-making in the context of short-range operational weather forecasting.
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    Is there a Tornado in Alex's Blood Flow? A Case Study for Narrative Medical Visualization
    (The Eurographics Association, 2022) Kleinau, Anna; Stupak, Evgenia; Mörth, Eric; Garrison, Laura A.; Mittenentzwei, Sarah; Smit, Noeska N.; Lawonn, Kai; Bruckner, Stefan; Gutberlet, Matthias; Preim, Bernhard; Meuschke, Monique; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
    Narrative visualization advantageously combines storytelling with new media formats and techniques, like interactivity, to create improved learning experiences. In medicine, it has the potential to improve patient understanding of diagnostic procedures and treatment options, promote confidence, reduce anxiety, and support informed decision-making. However, limited scientific research has been conducted regarding the use of narrative visualization in medicine. To explore the value of narrative visualization in this domain, we introduce a data-driven story to inform a broad audience about the usage of measured blood flow data to diagnose and treat cardiovascular diseases. The focus of the story is on blood flow vortices in the aorta, with which imaging technique they are examined, and why they can be dangerous. In an interdisciplinary team, we define the main contents of the story and the resulting design questions. We sketch the iterative design process and implement the story based on two genres. In a between-subject study, we evaluate the suitability and understandability of the story and the influence of different navigation concepts on user experience. Finally, we discuss reusable concepts for further narrative medical visualization projects.
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    Line Weaver: Importance-Driven Order Enhanced Rendering of Dense Line Charts
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Trautner, Thomas; Bruckner, Stefan; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Line charts are an effective and widely used technique for visualizing series of ordered two-dimensional data points. The relationship between consecutive points is indicated by connecting line segments, revealing potential trends or clusters in the underlying data. However, when dealing with an increasing number of lines, the render order substantially influences the resulting visualization. Rendering transparent lines can help but unfortunately the blending order is currently either ignored or naively used, for example, assuming it is implicitly given by the order in which the data was saved in a file. Due to the noncommutativity of classic alpha blending, this results in contradicting visualizations of the same underlying data set, so-called "hallucinators". In this paper, we therefore present line weaver, a novel visualization technique for dense line charts. Using an importance function, we developed an approach that correctly considers the blending order independently of the render order and without any prior sorting of the data. We allow for importance functions which are either explicitly given or implicitly derived from the geometric properties of the data if no external data is available. The importance can then be applied globally to entire lines, or locally per pixel which simultaneously supports various types of user interaction. Finally, we discuss the potential of our contribution based on different synthetic and real-world data sets where classic or naive approaches would fail.
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    MuSIC: Multi-Sequential Interactive Co-Registration for Cancer Imaging Data based on Segmentation Masks
    (The Eurographics Association, 2022) Eichner, Tanja; Mörth, Eric; Wagner-Larsen, Kari S.; Lura, Njål; Haldorsen, Ingfrid S.; Gröller, Eduard; Bruckner, Stefan; Smit, Noeska N.; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
    In gynecologic cancer imaging, multiple magnetic resonance imaging (MRI) sequences are acquired per patient to reveal different tissue characteristics. However, after image acquisition, the anatomical structures can be misaligned in the various sequences due to changing patient location in the scanner and organ movements. The co-registration process aims to align the sequences to allow for multi-sequential tumor imaging analysis. However, automatic co-registration often leads to unsatisfying results. To address this problem, we propose the web-based application MuSIC (Multi-Sequential Interactive Co-registration). The approach allows medical experts to co-register multiple sequences simultaneously based on a pre-defined segmentation mask generated for one of the sequences. Our contributions lie in our proposed workflow. First, a shape matching algorithm based on dual annealing searches for the tumor position in each sequence. The user can then interactively adapt the proposed segmentation positions if needed. During this procedure, we include a multi-modal magic lens visualization for visual quality assessment. Then, we register the volumes based on the segmentation mask positions. We allow for both rigid and deformable registration. Finally, we conducted a usability analysis with seven medical and machine learning experts to verify the utility of our approach. Our participants highly appreciate the multi-sequential setup and see themselves using MuSIC in the future.
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    Sunspot Plots: Model-based Structure Enhancement for Dense Scatter Plots
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Trautner, Thomas; Bolte, Fabian; Stoppel, Sergej; Bruckner, Stefan; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Scatter plots are a powerful and well-established technique for visualizing the relationships between two variables as a collection of discrete points. However, especially when dealing with large and dense data, scatter plots often exhibit problems such as overplotting, making the data interpretation arduous. Density plots are able to overcome these limitations in highly populated regions, but fail to provide accurate information of individual data points. This is particularly problematic in sparse regions where the density estimate may not provide a good representation of the underlying data. In this paper, we present sunspot plots, a visualization technique that communicates dense data as a continuous data distribution, while preserving the discrete nature of data samples in sparsely populated areas. We furthermore demonstrate the advantages of our approach on typical failure cases of scatter plots within synthetic and real-world data sets and validate its effectiveness in a user study.
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    VA-TRAC: Geospatial Trajectory Analysis for Monitoring, Identification, and Verification in Fishing Vessel Operations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Storm-Furru, Syver; Bruckner, Stefan; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    In order to ensure sustainability, fishing operations are governed by many rules and regulations that restrict the use of certain techniques and equipment, specify the species and size of fish that can be harvested, and regulate commercial activities based on licensing schemes. As the world's second largest exporter of fish and seafood products, Norway invests a significant amount of effort into maintaining natural ecosystem dynamics by ensuring compliance with its constantly evolving sciencebased regulatory body. This paper introduces VA-TRAC, a geovisual analytics application developed in collaboration with the Norwegian Directorate of Fisheries in order to address this complex task. Our approach uses automatic methods to identify possible catch operations based on fishing vessel trajectories, embedded in an interactive web-based visual interface used to explore the results, compare them with licensing information, and incorporate the analysts' domain knowledge into the decision making process. We present a data and task analysis based on a close collaboration with domain experts, and the design and implementation of VA-TRAC to address the identified requirements.