EG 2019 - Dirk Bartz Prize

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https://diglib7.eg.org/handle/10.2312/2632754
Preface and Table of Contents
1st Prize
Cytosplore: Interactive Visual Single-Cell Profiling of the Immune System
[full paper Image] [meta data Image]
Thomas Höllt, Nicola Pezzotti, Vincent van Unen, Na Li, Frits Koning, Elmar Eisemann, Boudewijn P. F. Lelieveldt, and Anna Vilanova
2nd Prize
Model-based Visualization for Medical Education and Training
[full paper Image] [meta data Image]
Noeska Smit, Kai Lawonn, Annelot Kraima, Marco deRuiter, Stefan Bruckner, Elmar Eisemann, and Anna Vilanova
3rd Prize
Visual Analytics for Epidemiology
[full paper Image] [meta data Image]
Bernhard Preim, Shiva Alemzadeh, Till Ittermann, Paul Klemm, Uli Niemann, and Myra Spiliopoulou

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    Cytosplore: Interactive Visual Single-Cell Profiling of the Immune System
    (The Eurographics Association, 2019) Höllt, Thomas; Pezzotti, Nicola; van Unen, Vincent; Li, Na; Koning, Frits; Eisemann, Elmar; Lelieveldt, Boudewijn P. F.; Vilanova, Anna; Bruckner, Stefan and Oeltze-Jafra, Steffen
    Recent advances in single-cell acquisition technology have led to a shift towards single-cell analysis in many fields of biology. In immunology, detailed knowledge of the cellular composition is of interest, as it can be the cause of deregulated immune responses, which cause diseases. Similarly, vaccination is based on triggering proper immune responses; however, many vaccines are ineffective or only work properly in a subset of those who are vaccinated. Identifying differences in the cellular composition of the immune system in such cases can lead to more precise treatment. Cytosplore is an integrated, interactive visual analysis framework for the exploration of large single-cell datasets. We have developed Cytosplore in close collaboration with immunology researchers and several partners use the software in their daily workflow. Cytosplore enables efficient data analysis and has led to several discoveries alongside high-impact publications.
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    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.
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    Visual Analytics for Epidemiology
    (The Eurographics Association, 2019) Preim, Bernhard; Alemzadeh, Shiva; Ittermann, Till; Klemm, Paul; Niemann, Uli; Spiliopoulou, Myra; Bruckner, Stefan and Oeltze-Jafra, Steffen
    We present visual analytics methods to analyze epidemiologic cohort studies. We consider the automatic identification of strong correlations and of subgroups that deviate from the global mean with respect to their risk for health disorders. Moreover, we tackle missing value problems and discuss appropriate imputation strategies and visual analytics support.
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    EUROGRAPHICS 2019: Dirk Bartz Prize Frontmatter
    (Eurographics Association, 2019) Bruckner, Stefan; Oeltze-Jafra, Steffen; Bruckner, Stefan and Oeltze-Jafra, Steffen