Stefan Bruckner is a full professor in Visualization at the Department of Informatics of the University of Bergen, Norway. He received his master's degree (2004) and Ph.D. (2008), both in Computer Science, from the TU Wien, Austria, and was awarded the habilitation (venia docendi) in Practical Computer Science in 2012. Before his appointment in Bergen in 2013, he was an assistant professor at the Institute of Computer Graphics and Algorithms of the TU Wien.
His research interests include all aspects of data visualization, with a particular focus on interactive techniques for the exploration and analysis of spatial data. He has made significant contributions to areas such as illustrative visualization, volume rendering, smart visual interfaces, biomedical data visualization, and visual parameter space exploration. In addition to his contributions in basic research, he has successfully led industry collaborations with major companies such as GE Healthcare and Agfa HealthCare, and has 6 granted patents.
He is a recipient of the Eurographics Young Researcher Award, the Karl-Heinz-Höhne Award for Medical Visualization, and his research has received 8 best paper awards and honorable mentions at international events. He was program co-chair of EuroVis, PacificVis, the Eurographics Workshop on Visual Computing for Biology and Medicine, the Eurographics Medical Prize, and serves on the editorial board of Computers & Graphics. He is an ACM Distinguished Speaker, and a member of ACM SIGGRAPH, Eurographics, and the IEEE Computer Society.
Please note that we are moving to new webpages, and not all content (e.g., publications) has been transferred yet . Please see our old pages for more complete information:
Publications
2019
![[PDF]](http://vis.uib.no/wp-content/plugins/papercite/img/pdf.png)
[Bibtex] @incollection {Bolte-2019-MVS,
author = {Bolte, Fabian and Bruckner, Stefan},
title = {Measures in Visualization Space},
booktitle = {Foundations of Data Visualization},
chapter = {3},
publisher = {Springer},
year = {2019},
pdf = {pdfs/Bolte-2019-MVS.pdf},
images = {images/Bolte-2019-MVS.png},
thumbnails = {images/Bolte-2019-MVS.png},
abstract = {Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches that evaluate particular aspects of individual visualization techniques, their perceptual characteristics, and even economic factors. Furthermore, there are approaches that attempt to provide means for measuring general properties of the visualization process as a whole. Measures can be quantitative or qualitative, and one of the primary goals is to provide objective means for reasoning about visualizations and their effectiveness. As such, they play a central role in the development of scientific theories for visualization. In this chapter, we provide an overview of the current state of the art, survey and classify different types of visualization measures, characterize their strengths and drawbacks, and provide an outline of open challenges for future research.},
note = {This is a preprint of a chapter for a planned book that was initiated by participants of the Dagstuhl Seminar 18041 ("Foundations of Data Visualization") and that is expected to be published by Springer. The final book chapter will differ from this preprint.}
url = {https://arxiv.org/abs/1909.05295}
}![[YT]](http://vis.uib.no/wp-content/papercite-data/images/youtube.png)
[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 9th EG Workshop on Visual Computing for Biology and Medicine (VCBM)},
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 = "https://youtu.be/Rzl7sl4WvdQ",
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 = "https://git.app.uib.no/Laura.Garrison/spectramosaic",
project = "VIDI"
}![[DOI]](http://vis.uib.no/wp-content/plugins/papercite/img/external.png){kind=small}
[Bibtex] @incollection{Smit-2019-AtlasVis,
title={Towards Advanced Interactive Visualization for Virtual Atlases},
author={Smit, Noeska and Bruckner, Stefan},
booktitle={Biomedical Visualisation},
pages={85--96},
year={2019},
publisher={Springer},
doi = {10.1007/978-3-030-19385-0_6},
url = "http://noeskasmit.com/wp-content/uploads/2019/07/Smit_AtlasVis_2019.pdf",
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"
}@article{Solteszova-2019-MLT,
author = {Solteszova, V. and Smit, N. N. and Stoppel, S. and Grüner, R. and Bruckner, S.},
title = {Memento: Localized Time-Warping for Spatio-Temporal Selection},
journal = {Computer Graphics Forum},
volume = {0},
number = {0},
pages = {},
year = {2019},
keywords = {interaction, temporal data, visualization, spatio-temporal projection, • Human-centred computing → Visualization techniques, Scientific visualization, • Mathematics of computing → Time series analysis},
images = "images/Solteszova-2019-MLT.jpg",
thumbnails = "images/Solteszova-2019-MLT-1.jpg",
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"
}@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 ’19)},
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 = "https://youtu.be/Rzl7sl4WvdQ",
project = "VIDI"
}@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"
}@ARTICLE {Stoppel-2019-LFL,
author = "Stoppel, Sergej and Bruckner, Stefan",
title = "LinesLab: A Flexible Low‐Cost Approach for the Generation of Physical Monochrome Art",
journal = "Computer Graphics Forum",
year = "2019",
abstract = "The desire for the physical generation of computer art has seen a significant body of research that has resulted in sophisticated robots and painting machines, together with specialized algorithms mimicking particular artistic techniques. The resulting setups are often expensive and complex, making them unavailable for recreational and hobbyist use. In recent years, however, a new class of affordable low‐cost plotters and cutting machines has reached the market. In this paper, we present a novel system for the physical generation of line and cut‐out art based on digital images, targeted at such off‐the‐shelf devices. Our approach uses a meta‐optimization process to generate results that represent the tonal content of a digital image while conforming to the physical and mechanical constraints of home‐use devices. By flexibly combining basic sets of positional and shape encodings, we are able to recreate a wide range of artistic styles. Furthermore, our system optimizes the output in terms of visual perception based on the desired viewing distance, while remaining scalable with respect to the medium size.",
pdf = "pdfs/Stoppel-2019-LFL.pdf",
images = "images/Stoppel-2019-LFL.jpg",
thumbnails = "images/Stoppel-2019-LFL.png",
publisher = "The Eurographics Association and John Wiley and Sons Ltd.",
doi = "10.1111/cgf.13609",
youtube = "https://www.youtube.com/watch?v=WdZJmU6fOAY",
project = "MetaVis"
}@ARTICLE {Bruckner-2019-DVM,
author = "Bruckner, Stefan",
title = "Dynamic Visibility‐Driven Molecular Surfaces",
journal = "Computer Graphics Forum",
year = "2019",
volume = "38",
number = "2",
abstract = "Molecular surface representations are an important tool for the visual analysis of molecular structure and function. In this paper, we present a novel method for the visualization of dynamic molecular surfaces based on the Gaussian model. In contrast to previous approaches, our technique does not rely on the construction of intermediate representations such as grids or triangulated surfaces. Instead, it operates entirely in image space, which enables us to exploit visibility information to efficiently skip unnecessary computations. With this visibility‐driven approach, we can visualize dynamic high‐quality surfaces for molecules consisting of millions of atoms. Our approach requires no preprocessing, allows for the interactive adjustment of all properties and parameters, and is significantly faster than previous approaches, while providing superior quality.",
pdf = "pdfs/Bruckner-2019-DVM.pdf",
images = "images/Bruckner-2019-DVM-1.jpg",
thumbnails = "images/Bruckner-2019-DVM.png",
publisher = "The Eurographics Association and John Wiley and Sons Ltd.",
doi = "10.1111/cgf.13640",
youtube = "https://www.youtube.com/watch?v=aZmDhTbJlAM",
git = "https://github.com/sbruckner/dynamol.git",
project = "MetaVis"
}![[VID]](http://vis.uib.no/wp-content/papercite-data/images/video.png)