DSpace Repository :: Browsing by Author "Bruckner, Stefan"

Browsing by Author "Bruckner, Stefan"

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Do Disease Stories need a Hero? Effects of Human Protagonists on a Narrative Visualization about Cerebral Small Vessel Disease
(The Eurographics Association and John Wiley & Sons Ltd., 2023) Mittenentzwei, Sarah; Weiß, Veronika; Schreiber, Stefanie; Garrison, Laura A.; Bruckner, Stefan; Pfister, Malte; Preim, Bernhard; Meuschke, Monique; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
Authors use various media formats to convey disease information to a broad audience, from articles and videos to interviews or documentaries. These media often include human characters, such as patients or treating physicians, who are involved with the disease. While artistic media, such as hand-crafted illustrations and animations are used for health communication in many cases, our goal is to focus on data-driven visualizations. Over the last decade, narrative visualization has experienced increasing prominence, employing storytelling techniques to present data in an understandable way. Similar to classic storytelling formats, narrative medical visualizations may also take a human character-centered design approach. However, the impact of this form of data communication on the user is largely unexplored. This study investigates the protagonist's influence on user experience in terms of engagement, identification, self-referencing, emotional response, perceived credibility, and time spent in the story. Our experimental setup utilizes a character-driven story structure for disease stories derived from Joseph Campbell's Hero's Journey. Using this structure, we generated three conditions for a cerebral small vessel disease story that vary by their protagonist: (1) a patient, (2) a physician, and (3) a base condition with no human protagonist. These story variants formed the basis for our hypotheses on the effect of a human protagonist in disease stories, which we evaluated in an online study with 30 participants. Our findings indicate that a human protagonist exerts various influences on the story perception and that these also vary depending on the type of protagonist.
EUROGRAPHICS 2017: Dirk Bartz Prize Frontmatter
(Eurographics Association, 2017) Bruckner, Stefan; Ropinski, Timo;
EUROGRAPHICS 2019: Dirk Bartz Prize Frontmatter
(Eurographics Association, 2019) Bruckner, Stefan; Oeltze-Jafra, Steffen; Bruckner, Stefan and Oeltze-Jafra, Steffen
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
EuroVis 2022 CGF 41-3 STARs: Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2022) Bruckner, Stefan; Turkay, Cagatay; Vrotsou, Katerina; Bruckner, Stefan; Turkay, Cagatay; Vrotsou, Katerina
Honeycomb Plots: Visual Enhancements for Hexagonal Maps
(The Eurographics Association, 2022) Trautner, Thomas; Sbardellati, Maximilian; Stoppel, Sergej; Bruckner, Stefan; Bender, Jan; Botsch, Mario; Keim, Daniel A.
Aggregation through binning is a commonly used technique for visualizing large, dense, and overplotted two-dimensional data sets. However, aggregation can hide nuanced data-distribution features and complicates the display of multiple data-dependent variables, since color mapping is the primary means of encoding. In this paper, we present novel techniques for enhancing hexplots with spatialization cues while avoiding common disadvantages of three-dimensional visualizations. In particular, we focus on techniques relying on preattentive features that exploit shading and shape cues to emphasize relative value differences. Furthermore, we introduce a novel visual encoding that conveys information about the data distributions or trends within individual tiles. Based on multiple usage examples from different domains and real-world scenarios, we generate expressive visualizations that increase the information content of classic hexplots and validate their effectiveness in a user study.
MedUse: A Visual Analysis Tool for Medication Use Data in the ABCD Study
(The Eurographics Association, 2019) Bartsch, Hauke; Garrison, Laura; Bruckner, Stefan; Wang, Ariel; Tapert, Susan F.; Grüner, Renate; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
The RxNorm vocabulary is a yearly-published biomedical resource providing normalized names for medications. It is used to capture medication use in the Adolescent Brain Cognitive Development (ABCD) study, an active and publicly available longitudinal research study following 11,800 children over 10 years. In this work, we present medUse, a visual tool allowing researchers to explore and analyze the relationship of drug category to cognitive or imaging derived measures using ABCD study data. Our tool provides position-based context for tree traversal and selection granularity of both study participants and drug category. Developed as part of the Data Exploration and Analysis Portal (DEAP), medUse is available to more than 600 ABCD researchers world-wide. By integrating medUse into an actively used research product we are able to reach a wide audience and increase the practical relevance of visualization for the biomedical field.
Model-based Visualization for Medical Education and Training
(The Eurographics Association, 2019) Smit, Noeska; Lawonn, Kai; Kraima, Annelot; deRuiter, Marco; Bruckner, Stefan; Eisemann, Elmar; Vilanova, Anna; Bruckner, Stefan and Oeltze-Jafra, Steffen
Anatomy, or the study of the structure of the human body, is an essential component of medical education. Certain parts of human anatomy are considered to be more complex to understand than others, due to a multitude of closely related structures. Furthermore, there are many potential variations in anatomy, e.g., different topologies of vessels, and knowledge of these variations is critical for many in medical practice. Some aspects of individual anatomy, such as the autonomic nerves, are not visible in individuals through medical imaging techniques or even during surgery, placing these nerves at risk for damage. 3D models and interactive visualization techniques can be used to improve understanding of this complex anatomy, in combination with traditional medical education paradigms. We present a framework incorporating several advanced medical visualization techniques and applications for teaching and training purposes, which is the result of an interdisciplinary project. In contrast to previous approaches which focus on general anatomy visualization or direct visualization of medical imaging data, we employ model-based techniques to represent variational anatomy, as well as anatomy not visible from imaging. Our framework covers the complete spectrum including general anatomy, anatomical variations, and anatomy in individual patients. Applications within our framework were evaluated positively with medical users, and our educational tool for general anatomy is in use in a Massive Open Online Course (MOOC) on anatomy, which had over 17000 participants worldwide in the first run.
Organic Narrative Charts
(The Eurographics Association, 2020) Bolte, Fabian; Bruckner, Stefan; Wilkie, Alexander and Banterle, Francesco
Storyline visualizations display the interactions of groups and entities and their development over time. Existing approaches have successfully adopted the general layout from hand-drawn illustrations to automatically create similar depictions. Ward Shelley is the author of several diagrammatic paintings that show the timeline of art-related subjects, such as Downtown Body, a history of art scenes. His drawings include many stylistic elements that are not covered by existing storyline visualizations, like links between entities, splits and merges of streams, and tags or labels to describe the individual elements. We present a visualization method that provides a visual mapping for the complex relationships in the data, creates a layout for their display, and adopts a similar styling of elements to imitate the artistic appeal of such illustrations.We compare our results to the original drawings and provide an open-source authoring tool prototype.
Output-Sensitive Filtering of Streaming Volume Data
(© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Solteszova, Veronika; Birkeland, Åsmund; Stoppel, Sergej; Viola, Ivan; Bruckner, Stefan; Chen, Min and Zhang, Hao (Richard)
Real‐time volume data acquisition poses substantial challenges for the traditional visualization pipeline where data enhancement is typically seen as a pre‐processing step. In the case of 4D ultrasound data, for instance, costly processing operations to reduce noise and to remove artefacts need to be executed for every frame. To enable the use of high‐quality filtering operations in such scenarios, we propose an output‐sensitive approach to the visualization of streaming volume data. Our method evaluates the potential contribution of all voxels to the final image, allowing us to skip expensive processing operations that have little or no effect on the visualization. As filtering operations modify the data values which may affect the visibility, our main contribution is a fast scheme to predict their maximum effect on the final image. Our approach prioritizes filtering of voxels with high contribution to the final visualization based on a maximal permissible error per pixel. With zero permissible error, the optimized filtering will yield a result that is identical to filtering of the entire volume. We provide a thorough technical evaluation of the approach and demonstrate it on several typical scenarios that require on‐the‐fly processing.Real‐time volume data acquisition poses substantial challenges for the traditional visualization pipeline where data enhancement is typically seen as a pre‐processing step. In the case of 4D ultrasound data, for instance, costly processing operations to reduce noise and to remove artefacts need to be executed for every frame. To enable the use of high‐quality filtering operations in such scenarios, we propose an outputsensitive approach to the visualization of streaming volume data. Our method evaluates the potential contribution of all voxels to the final image, allowing us to skip expensive processing operations that have little or no effect on the visualization As filtering operations modify the data values which may affect the visibility, our main contribution is a fast scheme to predict their maximum effect on the final image. Our approach prioritizes filtering of voxels with high contribution to the final visualization based on a maximal permissible error per pixel. With zero permissible error, the optimized filtering will yield a result that is identical to filtering of the entire volume. We provide a thorough technical evaluation of the approach and demonstrate it on several typical scenarios that require on‐the‐fly processing.
RadEx: Integrated Visual Exploration of Multiparametric Studies for Radiomic Tumor Profiling
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Mörth, Eric; Wagner-Larsen, Kari; Hodneland, Erlend; Krakstad, Camilla; Haldorsen, Ingfrid S.; Bruckner, Stefan; Smit, Noeska N.; Eisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lue
Better understanding of the complex processes driving tumor growth and metastases is critical for developing targeted treatment strategies in cancer. Radiomics extracts large amounts of features from medical images which enables radiomic tumor profiling in combination with clinical markers. However, analyzing complex imaging data in combination with clinical data is not trivial and supporting tools aiding in these exploratory analyses are presently missing. In this paper, we present an approach that aims to enable the analysis of multiparametric medical imaging data in combination with numerical, ordinal, and categorical clinical parameters to validate established and unravel novel biomarkers. We propose a hybrid approach where dimensionality reduction to a single axis is combined with multiple linked views allowing clinical experts to formulate hypotheses based on all available imaging data and clinical parameters. This may help to reveal novel tumor characteristics in relation to molecular targets for treatment, thus providing better tools for enabling more personalized targeted treatment strategies. To confirm the utility of our approach, we closely collaborate with experts from the field of gynecological cancer imaging and conducted an evaluation with six experts in this field.
SpectraMosaic: An Exploratory Tool for the Interactive Visual Analysis of Magnetic Resonance Spectroscopy Data
(The Eurographics Association, 2019) Garrison, Laura; Vašíček, Jakub; Grüner, Renate; Smit, Noeska N.; Bruckner, Stefan; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
Magnetic resonance spectroscopy (MRS) allows for assessment of tissue metabolite characteristics used often for early detection and treatment evaluation of brain-related pathologies. However, a steep learning curve for metabolite interpretation, paired with limited visualization tools, have constrained the more widespread adoption of MRS in clinical practice. In this design study, we collaborated with domain experts to design a novel visualization tool for the exploration of tissue metabolite concentration ratios in MRS clinical and research studies. We present a data and task analysis for this domain, with categorization of MRS data attributes into tiers of visual priority. We furthermore introduce a novel set of visual encodings for these attributes. Our result is SpectraMosaic (Figure 1), an interactive insight-generation tool for rapid exploration and comparison of metabolite ratios. We validate our approach with two case studies from MR spectroscopy experts, providing early qualitative evidence of the efficacy of the system and affording deeper insights into these complex data.
Trends & Opportunities in Visualization for Physiology: A Multiscale Overview
(The Eurographics Association and John Wiley & Sons Ltd., 2022) Garrison, Laura A.; Kolesar, Ivan; Viola, Ivan; Hauser, Helwig; Bruckner, Stefan; Bruckner, Stefan; Turkay, Cagatay; Vrotsou, Katerina
Combining elements of biology, chemistry, physics, and medicine, the science of human physiology is complex and multifaceted. In this report, we offer a broad and multiscale perspective on key developments and challenges in visualization for physiology. Our literature search process combined standard methods with a state-of-the-art visual analysis search tool to identify surveys and representative individual approaches for physiology. Our resulting taxonomy sorts literature on two levels. The first level categorizes literature according to organizational complexity and ranges from molecule to organ. A second level identifies any of three high-level visualization tasks within a given work: exploration, analysis, and communication. The findings of this report may be used by visualization researchers to understand the overarching trends, challenges, and opportunities in visualization for physiology and to provide a foundation for discussion and future research directions in this area.
A Visual Encoding System for Comparative Exploration of Magnetic Resonance Spectroscopy Data
(The Eurographics Association, 2019) Garrison, Laura; Vasicek, Jakub; Grüner, Renate; Smit, Noeska Natasja; Bruckner, Stefan; Madeiras Pereira, João and Raidou, Renata Georgia
Magnetic resonance spectroscopy (MRS) allows for assessment of tissue metabolite characteristics used often for early detection and treatment evaluation of intracranial pathologies. In particular, this non-invasive technique is important in the study of metabolic changes related to brain tumors, strokes, seizure disorders, Alzheimer's disease, depression, as well as other diseases and disorders affecting the brain. However, meaningful variations in ratios of tissue metabolites within a sample area are difficult to capture with current visualization tools. Furthermore, the learning curve to interpretation is steep and limits the more widespread adoption of MRS in clinical practice. In this work we present a novel, tiered visual encoding system for multidimensional MRS data to aid in the visual exploration of metabolite concentration ratios. Our system was developed in close collaboration with domain experts including detailed data and task analyses. This visual encoding system was subsequently realized as part of an interactive insight-generation tool for rapid exploration and comparison of metabolite ratio variation for deeper insights to these complex data.
Visual Exploration, Analysis, and Communication of Physiological Processes
(The Eurographics Association, 2023) Garrison, Laura A.; Bruckner, Stefan; Raidou, Renata; Kuhlen, Torsten
Describing the myriad biological processes occurring in living beings over time, the science of physiology is complex and critical to our understanding of how life works. Physiology spans many spatio-temporal scales to combine and bridge from the basic sciences (biology, physics, and chemistry) to medicine. Recent years have seen an explosion of new and finer-grained experimental and acquisition methods to characterize these data. The volume and complexity of these data necessitate effective visualizations to complement standard analysis practice. Visualization approaches must carefully consider and be adaptable to the user’s main task, be it exploratory, analytical, or communication-oriented. This research contributes to the areas of theory, empirical findings, methods, applications, and research replicability in visualizing physiology. Our overarching theme is the cross-disciplinary application of medical illustration and visualization techniques to address challenges in exploring, analyzing, and communicating aspects of human physiology to audiences with differing expertise.

Browsing by Author "Bruckner, Stefan"

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