Laura Garrison

Laura Garrison Bio Photo

Associate Professor

Visual Exploration & Communication

 Head Team Garrison

My research focuses on human factors in visualization, with a primary emphasis on the health and science domains. Specifically, I am interested in understanding how interaction, aesthetics, and storytelling strategies can impact the analysis and communication of complex information to different audiences and user groups.

I am also a professional biomedical artist, and worked for several years as an artist and content director in medical education start-ups in Silicon Valley, Chicago, and New York City. I love combining art, science, and technology to help people understand data or concepts, especially in the areas of biology and medicine. More recently, I’ve become interested in developing visualizations that are more accessible, i.e., usable and understandable, for different segments of the population.

I have a number of student projects available–if you are interested in working together, please reach out!

For more information on my research, feel free to browse my publications below or visit my personal website.




    [PDF] [DOI] [Bibtex]
    abstract = {With changing attitudes around knowledge, medicine, art, and technology, the human body has become a source of information and, ultimately, shareable and analyzable data. Centuries of illustrations and visualizations of the body occur within particular historical, social, and political contexts. These contexts are enmeshed in different so-called data cultures: ways that data, knowledge, and information are conceptualized and collected, structured and shared. In this work, we explore how information about the body was collected as well as the circulation, impact, and persuasive force of the resulting images. We show how mindfulness of data cultural influences remain crucial for today's designers, researchers, and consumers of visualizations. We conclude with a call for the field to reflect on how visualizations are not timeless and contextless mirrors on objective data, but as much a product of our time and place as the visualizations of the past.},
    author = {Correll, Michael and Garrison, Laura A.},
    booktitle = {arXiv, Proc CHI24},
    doi = {10.48550/arXiv.2402.05014},
    publisher = {arXiv},
    title = {When the Body Became Data: Historical Data Cultures and Anatomical Illustration},
    year = {2024},
    month = {Feb},
    pdf = {pdfs/garrisonCHI24.pdf},
    images = {images/garrisonCHI24.png},
    thumbnails = {images/garrisonCHI24.png},
    project = {VIDI}


    [PDF] [Bibtex]
    @MISC {balaka2023MoBaExplorer,
    booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine (Posters)},
    editor = {Garrison, Laura and Linares, Mathieu},
    title = {{MoBa Explorer: Enabling the navigation of data from the Norwegian Mother, Father, and Child cohort study (MoBa)}},
    author = {Balaka, Hanna and Garrison, Laura A. and Valen, Ragnhild and Vaudel, Marc},
    year = {2023},
    howpublished = {Poster presented at VCBM 2023.},
    publisher = {The Eurographics Association},
    abstract = {Studies in public health have generated large amounts of data helping researchers to better understand human diseases and improve patient care. The Norwegian Mother, Father and Child Cohort Study (MoBa) has collected information about pregnancy
    and childhood to better understand this crucial time of life. However, the volume of the data and its sensitive nature make its
    dissemination and examination challenging. We present a work-in-progress design study and accompanying web application,
    the MoBa Explorer, which presents aggregated MoBa study data genotypes and phenotypes. Our research explores how to
    serve two distinct purposes in one application: (1) allow researchers to interactively explore MoBa data to identify variables of
    interest for further study and (2) provide MoBa study details to an interested general public.},
    pdf = {pdfs/balaka2023MoBaExplorer.pdf},
    images = {images/balaka2023MoBaExplorer.png},
    thumbnails = {images/balaka2023MoBaExplorer-thumb.png},
    project = {VIDI}
    [PDF] [DOI] [Bibtex]
    @inproceedings {budich2023AIstories,
    booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
    editor = {Hansen, Christian and Procter, James and Renata G. Raidou and Jönsson, Daniel and Höllt, Thomas},
    title = {{Reflections on AI-Assisted Character Design for Data-Driven Medical Stories}},
    author = {Budich, Beatrice and Garrison, Laura A. and Preim, Bernhard and Meuschke, Monique},
    year = {2023},
    publisher = {The Eurographics Association},
    ISSN = {2070-5786},
    ISBN = {978-3-03868-216-5},
    DOI = {10.2312/vcbm.20231216},
    abstract = {Data-driven storytelling has experienced significant growth in recent years to become a common practice in various application areas, including healthcare. Within the realm of medical narratives, characters play a pivotal role in connecting audiences with data and conveying complex medical information in an engaging manner that may influence positive behavioral and lifestyle changes on the part of the viewer. However, the process of designing characters that are both informative and engaging remains a challenge. In this paper, we propose an AI-assisted pipeline for character design in the context of data-driven medical stories. Our iterative pipeline blends design sensibilities with automation to reduce the time and artistic expertise needed to develop characters reflective of the underlying data, even when that data is time-oriented as in a cohort study.},
    pdf = {pdfs/budichAIstories.pdf},
    images = {images/budichAIstories.png},
    thumbnails = {images/budichAIstories-thumb.png},
    project = {VIDI}
    [PDF] [DOI] [Bibtex]
    journal = {Computer Graphics Forum},
    title = {{Do Disease Stories need a Hero? Effects of Human Protagonists on a Narrative Visualization about Cerebral Small Vessel Disease}},
    author = {Mittenentzwei, Sarah and Weiß, Veronika and Schreiber, Stefanie and Garrison, Laura A. and Bruckner, Stefan and Pfister, Malte and Preim, Bernhard and Meuschke, Monique},
    year = {2023},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.14817},
    abstract = {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.},
    pdf = {pdfs/garrison-diseasestories.pdf},
    images = {images/garrison-diseasestories.png},
    thumbnails = {images/garrison-diseasestories-thumb.png},
    project = {VIDI}
    [PDF] [Bibtex]
    title = {Current Approaches in Narrative Medical Visualization},
    author = {Garrison, Laura Ann and Meuschke, Monique and Preim, Bernhard and Bruckner, Stefan},
    year = 2023,
    booktitle = {Approaches for Science Illustration and Communication},
    publisher = {Springer},
    address = {Gewerbestrasse 11, 6330 Cham, Switzerland},
    pages = {},
    note = {in publication},
    editor = {Mark Roughley},
    chapter = 4,
    pdf = {pdfs/garrison2023narrativemedvisbook.pdf},
    images = {images/garrison2023narrativemedvisbook.png},
    thumbnails = {images/garrison2023narrativemedvisbook-thumb.png},
    project = {VIDI}
    [PDF] [DOI] [Bibtex]
    title={Investigating user behavior in slideshows and scrollytelling as narrative genres in medical visualization},
    author={Mittenentzwei, Sarah and Garrison, Laura A and M{\"o}rth, Eric and Lawonn, Kai and Bruckner, Stefan and Preim, Bernhard and Meuschke, Monique},
    journal={Computers \& Graphics},
    abstract={In this study, we explore the impact of genre and navigation on user comprehension, preferences, and behaviors when experiencing data-driven disease stories. Our between-subject study (n=85) evaluated these aspects in-the-wild, with results pointing towards some general design considerations to keep in mind when authoring data-driven disease stories. Combining storytelling with interactive new media techniques, narrative medical visualization is a promising approach to communicating topics in medicine to a general audience in an accessible manner. For patients, visual storytelling may help them to better understand medical procedures and treatment options for more informed decision-making, boost their confidence and alleviate anxiety, and promote stronger personal health advocacy. Narrative medical visualization provides the building blocks for producing data-driven disease stories, which may be presented in several visual styles. These different styles correspond to different narrative genres, e.g., a Slideshow. Narrative genres can employ different navigational approaches. For instance, a Slideshow may rely on click interactions to advance through a story, while Scrollytelling typically uses vertical scrolling for navigation. While a common goal of a narrative medical visualization is to encourage a particular behavior, e.g., quitting smoking, it is unclear to what extent the choice of genre influences subsequent user behavior. Our study opens a new research direction into choice of narrative genre on user preferences and behavior in data-driven disease stories.},
    pdf = {pdfs/mittenentzwei2023userbehavior.pdf},
    images = {images/mittenentzwei2023userbehavior.png},
    thumbnails = {images/mittenentzwei2023userbehavior-thumb.png},
    project = {VIDI},
    [PDF] [DOI] [Bibtex]
    author={Garrison, Laura A. and Goodsell, David S. and Bruckner, Stefan},
    journal={IEEE Computer Graphics and Applications},
    title={Changing Aesthetics in Biomolecular Graphics},
    abstract={Aesthetics for the visualization of biomolecular structures have evolved over the years according to technological advances, user needs, and modes of dissemination. In this article, we explore the goals, challenges, and solutions that have shaped the current landscape of biomolecular imagery from the overlapping perspectives of computer science, structural biology, and biomedical illustration. We discuss changing approaches to rendering, color, human–computer interface, and narrative in the development and presentation of biomolecular graphics. With this historical perspective on the evolving styles and trends in each of these areas, we identify opportunities and challenges for future aesthetics in biomolecular graphics that encourage continued collaboration from multiple intersecting fields.},
    pdf = {pdfs/garrison-aestheticsmol.pdf},
    images = {images/garrison-aestheticsmol.png},
    thumbnails = {images/garrison-aestheticsmol-thumb.png},
    project = {VIDI}


    [PDF] [Bibtex]
    title = {
    From Molecules to the Masses: Visual Exploration, Analysis, and Communication
    of Human Physiology
    author = {Laura Ann Garrison},
    year = 2022,
    month = {September},
    isbn = 9788230841389,
    url = {},
    school = {Department of Informatics, University of Bergen, Norway},
    abstract = {
    The overarching theme of this thesis is the cross-disciplinary application of
    medical illustration and visualization techniques to address challenges in
    exploring, analyzing, and communicating aspects of physiology to audiences
    with differing expertise.
    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. It spans many spatio-temporal scales to combine and bridge
    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 thesis contributes to the areas of theory,
    empirical findings, methods, applications, and research replicability in
    visualizing physiology. Our contributions open with a state-of-the-art report
    exploring the challenges and opportunities in visualization for physiology.
    This report is motivated by the need for visualization researchers, as well
    as researchers in various application domains, to have a centralized,
    multiscale overview of visualization tasks and techniques. Using a
    mixed-methods search approach, this is the first report of its kind to
    broadly survey the space of visualization for physiology. Our approach to
    organizing the literature in this report enables the lookup of topics of
    interest according to spatio-temporal scale. It further subdivides works
    according to any combination of three high-level visualization tasks:
    exploration, analysis, and communication. This provides an easily-navigable
    foundation for discussion and future research opportunities for audience- and
    task-appropriate visualization for physiology. From this report, we identify
    two key areas for continued research that begin narrowly and subsequently
    broaden in scope: (1) exploratory analysis of multifaceted physiology data
    for expert users, and (2) communication for experts and non-experts alike.
    Our investigation of multifaceted physiology data takes place over two
    studies. Each targets processes occurring at different spatio-temporal scales
    and includes a case study with experts to assess the applicability of our
    proposed method. At the molecular scale, we examine data from magnetic
    resonance spectroscopy (MRS), an advanced biochemical technique used to
    identify small molecules (metabolites) in living tissue that are indicative
    of metabolic pathway activity. Although highly sensitive and specific, the
    output of this modality is abstract and difficult to interpret. Our design
    study investigating the tasks and requirements for expert exploratory
    analysis of these data led to SpectraMosaic, a novel application enabling
    domain researchers to analyze any permutation of metabolites in ratio form
    for an entire cohort, or by sample region, individual, acquisition date, or
    brain activity status at the time of acquisition. A second approach considers
    the exploratory analysis of multidimensional physiological data at the
    opposite end of the spatio-temporal scale: population. An effective
    exploratory data analysis workflow critically must identify interesting
    patterns and relationships, which becomes increasingly difficult as data
    dimensionality increases. Although this can be partially addressed with
    existing dimensionality reduction techniques, the nature of these techniques
    means that subtle patterns may be lost in the process. In this approach, we
    describe DimLift, an iterative dimensionality reduction technique enabling
    user identification of interesting patterns and relationships that may lie
    subtly within a dataset through dimensional bundles. Key to this method is
    the user's ability to steer the dimensionality reduction technique to follow
    their own lines of inquiry.
    Our third question considers the crafting of visualizations for communication
    to audiences with different levels of expertise. It is natural to expect that
    experts in a topic may have different preferences and criteria to evaluate a
    visual communication relative to a non-expert audience. This impacts the
    success of an image in communicating a given scenario. Drawing from diverse
    techniques in biomedical illustration and visualization, we conducted an
    exploratory study of the criteria that audiences use when evaluating a
    biomedical process visualization targeted for communication. From this study,
    we identify opportunities for further convergence of biomedical illustration
    and visualization techniques for more targeted visual communication design.
    One opportunity that we discuss in greater depth is the development of
    semantically-consistent guidelines for the coloring of molecular scenes. The
    intent of such guidelines is to elevate the scientific literacy of non-expert
    audiences in the context of molecular visualization, which is particularly
    relevant to public health communication.
    All application code and empirical findings are open-sourced and available
    for reuse by the scientific community and public. The methods and findings
    presented in this thesis contribute to a foundation of cross-disciplinary
    biomedical illustration and visualization research, opening several
    opportunities for continued work in visualization for physiology.
    pdf = {pdfs/garrison-phdthesis.pdf},
    images = {images/garrison-thesis.png},
    thumbnails = {images/garrison-thesis-thumb.png},
    project = {VIDI}
    [PDF] [DOI] [Bibtex]
    @inproceedings {Kleinau2022Tornado,
    booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
    editor = {Renata G. Raidou and Björn Sommer and Torsten W. Kuhlen and Michael Krone and Thomas Schultz and Hsiang-Yun Wu},
    title = {{Is there a Tornado in Alex's Blood Flow? A Case Study for Narrative Medical Visualization}},
    project = {ttmedvis},
    author = {Kleinau, Anna and Stupak, Evgenia and Mörth, Eric and Garrison, Laura A. and Mittenentzwei, Sarah and Smit, Noeska N. and Lawonn, Kai and Bruckner, Stefan and Gutberlet, Matthias and Preim, Bernhard and Meuschke, Monique},
    year = {2022},
    abstract = {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.},
    publisher = {The Eurographics Association},
    ISSN = {2070-5786},
    ISBN = {978-3-03868-177-9},
    DOI = {10.2312/vcbm.20221183},
    pdf = {pdfs/Kleinau_2022.pdf},
    thumbnails = {images/Kleinau_2022.PNG},
    images = {images/Kleinau_2022.PNG},
    [PDF] [DOI] [Bibtex]
    title = {Narrative medical visualization to communicate disease data},
    author = {Meuschke, Monique and Garrison, Laura A. and Smit, Noeska N. and Bach, Benjamin and Mittenentzwei, Sarah and Wei{\ss}, Veronika and Bruckner, Stefan and Lawonn, Kai and Preim, Bernhard},
    year = 2022,
    journal = {Computers & Graphics},
    volume = 107,
    pages = {144--157},
    doi = {10.1016/j.cag.2022.07.017},
    issn = {0097-8493},
    url = {},
    abstract = {This paper explores narrative techniques combined with medical visualizations to tell data-driven stories about diseases for a general audience. The field of medical illustration uses narrative visualization through hand-crafted techniques to promote health literacy. However, data-driven narrative visualization has rarely been applied to medical data. We derived a template for creating stories about diseases and applied it to three selected diseases to demonstrate how narrative techniques could support visual communication and facilitate understanding of medical data. One of our main considerations is how interactive 3D anatomical models can be integrated into the story and whether this leads to compelling stories in which the users feel involved. A between-subject study with 90 participants suggests that the combination of a carefully designed narrative structure, the constant involvement of a specific patient, high-qualitative visualizations combined with easy-to-use interactions, are critical for an understandable story about diseases that would be remembered by participants.},
    pdf = {pdfs/Narrative_medical_MEUSCHKE_DOA18072022_AFV.pdf},
    thumbnails = {images/Meuschke2022narrative-thumb.png},
    images = {images/Meuschke2022narrative.png},
    project = {VIDI}
    [PDF] [Bibtex]
    title = {Content-Driven Layout for Visualization Design},
    author = {Kristiansen, Yngve and Garrison, Laura and Bruckner, Stefan},
    year = 2022,
    journal = {Proceedings of the International Symposium on Visual Information Communication and Interaction (to appear)},
    volume = {},
    pages = {},
    doi = {},
    issn = {},
    url = {},
    abstract = {Multi-view visualizations are typically presented in a grid layout with elements positioned according to their bounding rectangles. These rectangles often contain unused white space. In cases where Tufte’s Shrink Principle can be applied to reduce non-data-ink without impairing the communication of information, unused white space can be utilized for the placement of other elements. This is often done in manually “hand-crafted” layouts by designers. However, upon changes to individual elements, this design process has to be repeated. To reduce non-data-ink and repetitive manual design, we contribute a method for automatically turning a grid layout into a content-driven layout, where elements are positioned with respect to their contents. Existing approaches have explored the use of a force simulation in conjunction with proxy geometries to simplify collision handling for irregular shapes. Such customized force directed layouts are usually unstable, and often require additional constraints to run properly. In addition, proxy geometries become less accurate and effective with more irregular shapes. To solve these shortcomings, we contribute an approach for identifying central elements in an original grid layout in order to set up corresponding attractive forces. Furthermore, we utilize an imagebased approach for collision detection and avoidance that works accurately for highly irregular shapes. We demonstrate the utility of our approach with three case studies.},
    images = "images/Kristiansen-2022-LungsDt.PNG",
    thumbnails = "images/Kristiansen-2022-LungsDt.PNG",
    pdf = {pdfs/Kristiansen-2022-CDL.pdf},
    project = "MetaVis",
    [PDF] [DOI] [Bibtex]
    @ARTICLE {Garrison2022MolColor,
    author = "Laura A. Garrison and Stefan Bruckner",
    title = "Considering Best Practices in Color Palettes for Molecular Visualizations",
    journal = "Journal of Integrative Bioinformatics",
    year = "2022",
    abstract = "Biomedical illustration and visualization techniques provide a window into complex molecular worlds that are difficult to capture through experimental means alone. Biomedical illustrators frequently employ color to help tell a molecular story, e.g., to identify key molecules in a signaling pathway. Currently, color use for molecules is largely arbitrary and often chosen based on the client, cultural factors, or personal taste. The study of molecular dynamics is relatively young, and some stakeholders argue that color use guidelines would throttle the growth of the field. Instead, content authors have ample creative freedom to choose an aesthetic that, e.g., supports the story they want to tell. However, such creative freedom comes at a price. The color design process is challenging, particularly for those without a background in color theory. The result is a semantically inconsistent color space that reduces the interpretability and effectiveness of molecular visualizations as a whole. Our contribution in this paper is threefold. We first discuss some of the factors that contribute to this array of color palettes. Second, we provide a brief sampling of color palettes used in both industry and research sectors. Lastly, we suggest considerations for developing best practices around color palettes applied to molecular visualization.",
    images = "images/garrison-molecularcolor-full.png",
    thumbnails = "images/garrison-molecularcolor-thumb.png",
    pdf = "pdfs/garrison-molecularcolor.pdf",
    publisher = "De Gruyter",
    doi = "10.1515/jib-2022-0016",
    project = "VIDI"
    [PDF] [DOI] [Bibtex]
    @ARTICLE {Garrison2022PhysioSTAR,
    author = "Laura A. Garrison and Ivan Kolesar and Ivan Viola and Helwig Hauser and Stefan Bruckner",
    title = "Trends & Opportunities in Visualization for Physiology: A Multiscale Overview",
    journal = "Computer Graphics Forum",
    year = "2022",
    volume = "41",
    number = "3",
    publisher = "The Eurographics Association and John Wiley & Sons Ltd.",
    pages = "609-643",
    doi = "10.1111/cgf.14575",
    abstract = "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. ",
    images = "images/garrison-STAR-taxonomy.png",
    thumbnails = "images/garrison-STAR-thumb.png",
    pdf = "pdfs/Garrison_STAR_cameraready.pdf",
    publisher = "The Eurographics Association and John Wiley \& Sons Ltd.",
    project = "VIDI"


    [PDF] [DOI] [VID] [Bibtex]
    author = {Kristiansen, Y. S. and Garrison, L. and Bruckner, S.},
    title = {Semantic Snapping for Guided Multi-View Visualization Design},
    journal = {IEEE Transactions on Visualization and Computer Graphics},
    year = {2021},
    volume = {},
    pages = {},
    doi = {},
    abstract = {Visual information displays are typically composed of multiple visualizations that are used to facilitate an understanding of the underlying data. A common example are dashboards, which are frequently used in domains such as finance, process monitoring and business intelligence. However, users may not be aware of existing guidelines and lack expert design knowledge when composing such multi-view visualizations. In this paper, we present semantic snapping, an approach to help non-expert users design effective multi-view visualizations from sets of pre-existing views. When a particular view is placed on a canvas, it is “aligned” with the remaining views–not with respect to its geometric layout, but based on aspects of the visual encoding itself, such as how data dimensions are mapped to channels. Our method uses an on-the-fly procedure to detect and suggest resolutions for conflicting, misleading, or ambiguous designs, as well as to provide suggestions for alternative presentations. With this approach, users can be guided to avoid common pitfalls encountered when composing visualizations. Our provided examples and case studies demonstrate the usefulness and validity of our approach.},
    note = {Accepted for publication, to be presented at IEEE VIS 2021},
    project = {MetaVis,VIDI},
    pdf = {pdfs/Kristiansen-2021-SSG.pdf},
    vid = {vids/Kristiansen-2021-SSG.mp4},
    thumbnails = {images/Kristiansen-2021-SSG.png},
    images = {images/Kristiansen-2021-SSG.jpg},
    keywords = {tabular data, guidelines, mixed initiative human-machine analysis, coordinated and multiple views},
    doi = {10.1109/TVCG.2021.3114860},
    [PDF] [Bibtex]
    author = {Laura Garrison and Monique Meuschke and Jennifer Fairman and Noeska Smit and Bernhard Preim and Stefan Bruckner},
    title = {An Exploration of Practice and Preferences for the Visual Communication of Biomedical Processes},
    booktitle = {Proceedings of VCBM},
    year = {2021},
    pages = {},
    doi = {},
    abstract = {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.
    Best Paper Honorable Mention at VCBM 2021},
    note = {Accepted for publication, to be presented at VCBM 2021},
    project = {VIDI,ttmedvis},
    pdf = {pdfs/Garrison-2021-EPP.pdf},
    thumbnails = {images/Garrison-2021-EPP.png},
    images = {images/Garrison-2021-EPP.jpg},
    url = {},
    keywords = {biomedical illustration, visual communication, survey},
    [PDF] [DOI] [YT] [Bibtex]
    @ARTICLE {Garrison-2021-DimLift,
    author = {Garrison, Laura and M\"{u}ller, Juliane and Schreiber, Stefanie and Oeltze-Jafra, Steffen and Hauser, Helwig and Bruckner, Stefan},
    title = {DimLift: Interactive Hierarchical Data Exploration through Dimensional Bundling},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    year = {2021},
    abstract = {The identification of interesting patterns and relationships is essential to exploratory data analysis. This becomes increasingly difficult in high dimensional datasets. While dimensionality reduction techniques can be utilized to reduce the analysis space, these may unintentionally bury key dimensions within a larger grouping and obfuscate meaningful patterns. With this work we introduce DimLift, a novel visual analysis method for creating and interacting with dimensional bundles. Generated through an iterative dimensionality reduction or user-driven approach, dimensional bundles are expressive groups of dimensions that contribute similarly to the variance of a dataset. Interactive exploration and reconstruction methods via a layered parallel coordinates plot allow users to lift interesting and subtle relationships to the surface, even in complex scenarios of missing and mixed data types. We exemplify the power of this technique in an expert case study on clinical cohort data alongside two additional case examples from nutrition and ecology.},
    volume = {27},
    number = {6},
    pages = {2908--2922},
    pdf = {pdfs/garrison-2021-dimlift.pdf},
    images = {images/garrison_dimlift.jpg},
    thumbnails = {images/garrison_dimlift_thumb.jpg},
    youtube = {},
    doi = {10.1109/TVCG.2021.3057519},
    git = {},
    project = {VIDI},
    [PDF] [DOI] [Bibtex]
    @ARTICLE {Mueller-2021-IDA,
    author = {M\"{u}ller, Juliane and Garrison, Laura and Ulbrich, Philipp and Schreiber, Stefanie and Bruckner, Stefan and Hauser, Helwig and Oeltze-Jafra, Steffen},
    title = {Integrated Dual Analysis of Quantitative and Qualitative High-Dimensional Data},
    journal={IEEE Transactions on Visualization and Computer Graphics},
    year = {2021},
    abstract = {The Dual Analysis framework is a powerful enabling technology for the exploration of high dimensional quantitative data by treating data dimensions as first-class objects that can be explored in tandem with data values. In this work, we extend the Dual Analysis framework through the joint treatment of quantitative (numerical) and qualitative (categorical) dimensions. Computing common measures for all dimensions allows us to visualize both quantitative and qualitative dimensions in the same view. This enables a natural joint treatment of mixed data during interactive visual exploration and analysis. Several measures of variation for nominal qualitative data can also be applied to ordinal qualitative and quantitative data. For example, instead of measuring variability from a mean or median, other measures assess inter-data variation or average variation from a mode. In this work, we demonstrate how these measures can be integrated into the Dual Analysis framework to explore and generate hypotheses about high-dimensional mixed data. A medical case study using clinical routine data of patients suffering from Cerebral Small Vessel Disease (CSVD), conducted with a senior neurologist and a medical student, shows that a joint Dual Analysis approach for quantitative and qualitative data can rapidly lead to new insights based on which new hypotheses may be generated.},
    volume = {27},
    number = {6},
    pages = {2953--2966},
    pdf = {pdfs/Mueller_2020_IDA.pdf},
    images = {images/Mueller_2020_IDA.jpg},
    thumbnails = {images/Mueller_2020_IDA.png},
    doi = {10.1109/TVCG.2021.3056424},
    git = {},
    project = {VIDI},


    [PDF] [DOI] [Bibtex]
    author = {Garrison, Laura and Va\v{s}\'{i}\v{c}ek, Jakub and Craven, Alex R. and Gr\"{u}ner, Renate and Smit, Noeska and Bruckner, Stefan},
    title = {Interactive Visual Exploration of Metabolite Ratios in MR Spectroscopy Studies},
    journal = {Computers \& Graphics},
    volume = {92},
    pages = {1--12},
    keywords = {medical visualization, magnetic resonance spectroscopy data, information visualization, user-centered design},
    doi = {10.1016/j.cag.2020.08.001},
    abstract = {Magnetic resonance spectroscopy (MRS) is an advanced biochemical technique used to identify metabolic compounds in living tissue. While its sensitivity and specificity to chemical imbalances render it a valuable tool in clinical assessment, the results from this modality are abstract and difficult to interpret. With this design study we characterized and explored the tasks and requirements for evaluating these data from the perspective of a MRS research specialist. Our resulting tool, SpectraMosaic, links with upstream spectroscopy quantification software to provide a means for precise interactive visual analysis of metabolites with both single- and multi-peak spectral signatures. Using a layered visual approach, SpectraMosaic allows researchers to analyze any permutation of metabolites in ratio form for an entire cohort, or by sample region, individual, acquisition date, or brain activity status at the time of acquisition. A case study with three MRS researchers demonstrates the utility of our approach in rapid and iterative spectral data analysis.},
    year = {2020},
    pdf = "pdfs/Garrison-2020-IVE.pdf",
    thumbnails = "images/Garrison-2020-IVE.png",
    images = "images/Garrison-2020-IVE.jpg",
    project = "VIDI",
    git = "",


    [PDF] [DOI] [Bibtex]
    @inproceedings {Bartsch-2019-MVA,
    booktitle = {Proceedings of VCBM 2019 (Short Papers)},
    title = {MedUse: A Visual Analysis Tool for Medication Use Data in the ABCD Study},
    author = {Bartsch, Hauke and Garrison, Laura and Bruckner, Stefan and Wang, Ariel and Tapert, Susan F. and Gr\"{u}ner, Renate},
    abstract = {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.},
    year = {2019},
    pages = {97--101},
    images = "images/Bartsch-2019-MVA.jpg",
    thumbnails = "images/Bartsch-2019-MVA.png",
    pdf = "pdfs/Bartsch-2019-MVA.pdf",
    publisher = {The Eurographics Association},
    ISSN = {2070-5786},
    ISBN = {978-3-03868-081-9},
    DOI = {10.2312/vcbm.20191236},
    project = {VIDI}
    [PDF] [DOI] [YT] [Bibtex]
    @INPROCEEDINGS {Garrison2019SM,
    author = {Garrison, Laura and Va\v{s}\'{\i}\v{c}ek, Jakub and Gr\"{u}ner, Renate and Smit, Noeska and Bruckner, Stefan},
    title = {SpectraMosaic: An Exploratory Tool for the Interactive Visual Analysis of Magnetic Resonance Spectroscopy Data},
    journal = {Computer Graphics Forum},
    month = {sep},
    year = {2019},
    booktitle = {Proceedings of VCBM 2019},
    pages = {1--10},
    event = "VCBM 2019",
    proceedings = "Proceedings of the 9th Eurographics Workshop on Visual Computing in Biology and Medicine",
    keywords = {medical visualization, magnetic resonance spectroscopy data, information visualization, user-centered design},
    images = "images/garrison_VCBM19spectramosaic_full.PNG",
    thumbnails = "images/garrison_VCBM19spectramosaic_thumb.png",
    pdf = "pdfs/garrison_VCBM19spectramosaic.pdf",
    youtube = "",
    abstract = {Magnetic resonance spectroscopy (MRS) allows for assessment of tissue metabolite characteristics used often for early detection and treatment evaluation of brain-related pathologies. 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 design study, we collaborated with domain experts to design a novel visualization tool for the exploration of tissue metabolite concentration ratios in spectroscopy clinical and research studies. We present a data and task analysis for this domain, where MRS data attributes can be categorized into tiers of visual priority. We furthermore introduce a novel set of visual encodings for these attributes. Our result is SpectraMosaic (see Figure~\ref{fig:teaser}), 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 for visualization of spectral data and affording deeper insights into these complex heterogeneous data.},
    git = "",
    doi = "0.2312/vcbm.20191225",
    project = "VIDI"
    [PDF] [YT] [Bibtex]
    @MISC {Garrison2019SM_eurovis,
    title = {A Visual Encoding System for Comparative Exploration of Magnetic Resonance Spectroscopy Data},
    author = {Garrison, Laura and Va\v{s}\'{\i}\v{c}ek, Jakub and Gr\"{u}ner, Renate and Smit, Noeska and Bruckner, Stefan},
    abstract = "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 multi-dimensional 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.",
    booktitle = {Proceedings of the EuroVis Conference - Posters (EuroVis 2019)},
    year = {2019},
    howpublished = "Poster presented at the EuroVis conference 2019",
    keywords = {medical visualization, magnetic resonance spectroscopy data, information visualization, user-centered design},
    images = "images/garrison_eurovis2019_SM_encodings.png",
    thumbnails = "images/garrison_eurovis2019_SM_encodings.png",
    pdf = "pdfs/garrison_eurovis2019_SM.pdf",
    youtube = "",
    project = "VIDI"