VIDI: Visual Data Science for Large Scale Hypothesis Management in Imaging Biomarker Discovery

Project Overview

Technology is revolutionizing medicine. New scanners enable doctors to “look into the patient’s body” and study their anatomy and physiology without the need of a scalpel. At an amazing speed new scanning technologies emerge, providing an ever growing and increasingly varied look into medical conditions. Today, we cannot “only” look at the bones within a body, but we can also examine soft tissue, blood flow, activation networks in the brain, and many more aspects of anatomy and physiology. The increased amount and complexity of the acquired medical imaging data leads to new challenges in knowledge extraction and decision making.

In order to optimally exploit this new wealth of information, it is crucial that all this imaging data is successfully linked to the medical condition of the patient. In many cases, this is challenging, for example, when diagnosing early-stage cancer or mental disorders. Analogous to biomarkers, which are molecular structures that are used to identify medical conditions, imaging biomarkers are information structures in medical images that can help with diagnostics and treatment planning, formulated in terms of features that can be computed from the imaging data. Imaging biomarker discovery is a highly challenging task and traditionally only a single hypothesis (for a new biomarker) is examined at a time.

This makes it impossible to explore a large number as well as more complex imaging biomarkers across multi-aspect data. In the VIDI project, we propose to research and advance visual data science to improve imaging biomarker discovery through the visual integration of multi-aspect medical data with a new visualization-enabled hypothesis management framework.

We aim to reduce the time it takes to discover new imaging biomarkers by studying structured sets of hypotheses, to be examined at the same time, through the integration of computational approaches and interactive visual analysis techniques. Another related goal is to enable the discovery of more complex imaging biomarkers, across multiple modalities, that potentially are able to more accurately characterize diseases. This should lead to a new form of designing innovative and effective imaging protocols and to the discovery of new imaging biomarkers, improving suboptimal imaging protocols and thus also reducing scanning costs. Our project is a truly interdisciplinary research effort, bringing visualization research and imaging research together in one project, and this is perfectly suited for the novel Centre for Medical Imaging and Visualization that has been established in Bergen, Norway.

VIDI Approach

To achieve these goals we have divided the VIDI project into seven discrete workpackages (WP), which can be executed, to some extent, in parallel:

WP1: Hypothesis management
Research and design of methodologies necessary for structuring, representation, exploration, and analysis of hypothesis sets. Develop visual language for data interactions and methods for linking spatial with non-spatial data.

WP2: Data & Features
Exploration of medical image feature extraction and visualisation, definition of UX for selection and refinement of data features to extend into additional dimensions.

WP3: Hypotheses Scoring
Development of methods for interactive visual ranking and analyses of user hypotheses sets. Exploration of methods to provide user with evaluation preview of investigated hypotheses, linked to hypotheses visualisation and rankings.

WP4: Optimized Imaging
Evaluation of existing imaging protocols and development new imaging techniques. Investigation of imaging process to guard against suboptimal image acquisitions.

WP5: Integration
Integrate solutions from work packages 1-4.

WP6: Evalulation
Evaluate new hypothesis methods in context of three target applications: 1) gynecologic cancer; 2) neuroinflammation in MS; and 3) neurodegenerative disorders.

WP7: Management & Dissemination
Coordination between the involved partners, planning and reporting, and dissemination.

VIDI Project Team

PI: Helwig Hauser
Co-PIs: Stefan Bruckner and Renate Grüner, MMIV
Associated researcher: Noeska Smit
PhD students: Laura Garrison and Fourough Gharbalchi

This project is funded by the Bergen Research Foundation (BFS) and the University of Bergen.



    [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]
    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] [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]
    author = {Solteszova, V. and Smit, N. N. and Stoppel, S. and Gr\"{u}ner, R. and Bruckner, S.},
    title = {Memento: Localized Time-Warping for Spatio-Temporal Selection},
    journal = {Computer Graphics Forum},
    volume = {39},
    number = {1},
    pages = {231--243},
    year = {2020},
    keywords = {interaction, temporal data, visualization, spatio-temporal projection},
    images = "images/Solteszova-2019-MLT.jpg",
    thumbnails = "images/Solteszova-2019-MLT-1.jpg",
    pdf = "pdfs/Solteszova-2019-MLT.pdf",
    doi = {10.1111/cgf.13763},
    abstract = {Abstract Interaction techniques for temporal data are often focused on affecting the spatial aspects of the data, for instance through the use of transfer functions, camera navigation or clipping planes. However, the temporal aspect of the data interaction is often neglected. The temporal component is either visualized as individual time steps, an animation or a static summary over the temporal domain. When dealing with streaming data, these techniques are unable to cope with the task of re-viewing an interesting local spatio-temporal event, while continuing to observe the rest of the feed. We propose a novel technique that allows users to interactively specify areas of interest in the spatio-temporal domain. By employing a time-warp function, we are able to slow down time, freeze time or even travel back in time, around spatio-temporal events of interest. The combination of such a (pre-defined) time-warp function and brushing directly in the data to select regions of interest allows for a detailed review of temporally and spatially localized events, while maintaining an overview of the global spatio-temporal data. We demonstrate the utility of our technique with several usage scenarios.},
    project = "MetaVis,ttmedvis,VIDI"


    [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"
    [DOI] [Bibtex]
    title={Towards Advanced Interactive Visualization for Virtual Atlases},
    author={Smit, Noeska and Bruckner, Stefan},
    booktitle={Biomedical Visualisation},
    doi = {10.1007/978-3-030-19385-0_6},
    url = "",
    images = "images/Smit-2019-AtlasVis.png",
    thumbnails = "images/Smit-2019-AtlasVis.png",
    abstract = "An atlas is generally defined as a bound collection of tables, charts or illustrations describing a phenomenon. In an anatomical atlas for example, a collection of representative illustrations and text describes anatomy for the purpose of communicating anatomical knowledge. The atlas serves as reference frame for comparing and integrating data from different sources by spatially or semantically relating collections of drawings, imaging data, and/or text. In the field of medical image processing, atlas information is often constructed from a collection of regions of interest, which are based on medical images that are annotated by domain experts. Such an atlas may be employed for example for automatic segmentation of medical imaging data. The combination of interactive visualization techniques with atlas information opens up new possibilities for content creation, curation, and navigation in virtual atlases. With interactive visualization of atlas information, students are able to inspect and explore anatomical atlases in ways that were not possible with the traditional method of presenting anatomical atlases in book format, such as viewing the illustrations from other viewpoints. With advanced interaction techniques, it becomes possible to query the data that forms the basis for the atlas, thus empowering researchers to access a wealth of information in new ways. So far, atlasbased visualization has been employed for mainly medical education, as well as biological research. In this survey, we provide an overview of current digital biomedical atlas tasks and applications and summarize relevant visualization techniques. We discuss recent approaches for providing next-generation visual interfaces to navigate atlas data that go beyond common text-based search and hierarchical lists. Finally, we reflect on open challenges and opportunities for the next steps in interactive atlas visualization. ",
    project = "ttmedvis,MetaVis,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"
    [PDF] [DOI] [Bibtex]
    @inproceedings {Smit-2019-DBP,
    booktitle = {Eurographics 2019 - Dirk Bartz Prize},
    editor = {Bruckner, Stefan and Oeltze-Jafra, Steffen},
    title = {{Model-based Visualization for Medical Education and Training}},
    author = {Smit, Noeska and Lawonn, Kai and Kraima, Annelot and deRuiter, Marco and Bruckner, Stefan and Eisemann, Elmar and Vilanova, Anna},
    year = {2019},
    publisher = {The Eurographics Association},
    ISSN = {1017-4656},
    DOI = {10.2312/egm.20191033},
    pdf = "pdfs/Smit_DBPrize_2019.pdf",
    images = "images/Smit_DBPrize_2019.png",
    thumbnails = "images/Smit_DBPrize_2019.png",
    abstract = "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.",
    project = "ttmedvis,VIDI"
    [PDF] [DOI] [Bibtex]
    @inproceedings {Moerth-2019-VCBM,
    booktitle = "Eurographics Workshop on Visual Computing for Biology and Medicine",
    editor = "Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia",
    abstract = "Three-dimensional (3D) ultrasound imaging and visualization
    is often used in medical diagnostics, especially in prenatal
    screening. Screening the development of the fetus is
    important to assess possible complications early on. State
    of the art approaches involve taking standardized
    measurements to compare them with standardized tables. The
    measurements are taken in a 2D slice view, where precise
    measurements can be difficult to acquire due to the fetal
    pose. Performing the analysis in a 3D view would enable the
    viewer to better discriminate between artefacts and
    representative information. Additionally making data
    comparable between different investigations and patients is
    a goal in medical imaging techniques and is often achieved
    by standardization. With this paper, we introduce a novel
    approach to provide a standardization method for 3D
    ultrasound fetus screenings. Our approach is called “The
    Vitruvian Baby” and incorporates a complete pipeline for
    standardized measuring in fetal 3D ultrasound. The input of
    the method is a 3D ultrasound screening of a fetus and the
    output is the fetus in a standardized T-pose. In this pose,
    taking measurements is easier and comparison of different
    fetuses is possible. In addition to the transformation of
    the 3D ultrasound data, we create an abstract representation
    of the fetus based on accurate measurements. We demonstrate
    the accuracy of our approach on simulated data where the
    ground truth is known.",
    title = "The Vitruvian Baby: Interactive Reformation of Fetal Ultrasound Data to a T-Position",
    author = "M\"{o}rth, Eric and Raidou, Renata Georgia and Viola, Ivan and Smit, Noeska",
    year = "2019",
    publisher = "The Eurographics Association",
    ISSN = "2070-5786",
    ISBN = "978-3-03868-081-9",
    DOI = "10.2312/vcbm.20191245",
    pdf = "pdfs/VCBM_TheVitruvianBaby_ShortPaper_201-205.pdf",
    images = "images/vcbmVitruvianBaby.jpg",
    thumbnails = "images/vcbmVitruvianBaby.jpg",
    url = "",
    project = {VIDI}


    [PDF] [Bibtex]
    @MISC {Smit18MMIV,
    author = "N. N. Smit and S. Bruckner and H. Hauser and I. Haldorsen and A. Lundervold and A. S. Lundervold and E. Hodneland and L. Oltedal and K. Specht and E. R. Gruner",
    title = "Research Agenda of the Mohn Medical Imaging and Visualization Centre in Bergen, Norway",
    howpublished = "Poster presented at the EG VCBM workshop 2018",
    month = "September",
    year = "2018",
    abstract = "The Mohn Medical Imaging and Visualization Centre (MMIV) was recently established in collaboration between the University of Bergen, Norway, and the Haukeland University Hospital in Bergen with generous financial support from the Bergen Research Foundation (BFS) to conduct cross-disciplinary research related to state-of-the-art medical imaging, including preclinical and clinical high-field MRI, CT and hybrid PET/CT/MR.The overall goal of the Centre is to research new methods in quantitative imaging and interactive visualization to predict changes in health and disease across spatial and temporal scales. This encompasses research in feature detection, feature extraction, and feature prediction, as well as on methods and techniques for the interactive visualization of spatial and abstract data related to and derived from these features.With special emphasis on the natural and medical sciences, the long-term goal of the Centre is to consolidate excellence in the interplay between medical imaging (physics, chemistry, radiography, radiology), and visualization (computer science and mathematics) and develop novel and refined imaging methods that may ultimately improve patient care. In this poster, we describe the overall research agenda of MMIV and describe the four core projects in the centre.",
    pdf = "pdfs/smit2018posterabstract.pdf",
    images = "images/MMIVPoster.png",
    thumbnails = "images/MMIVPoster.png",
    location = "Granada, Spain",
    project = "VIDI"