Tenure-Track Position in Medical Visualization

This grant substantiates a tenure track position supported by Bergen Research Foundation and the University of Bergen. Noeska Smit from the Netherlands started in her position as associate professor at the Department of Informatics, UiB, January 1, 2017. Smit’s specialty is in medical visualization. The recruitment of Smit is part of a joint priority of the field of medical visualization at Helse Bergen and University of Bergen. The common priority also has resulted in the establishment of a joint center for medical imaging and visualization located at Helse Bergen This center is also supported economically by Bergen Research Foundation.

The visualization group at Department of Informatics has a leading position in the visualization of complex data from numerous application domains and is actively engaged in research in the emerging field of computational medicine. The recruitment of Smit is a strategic move towards this field and represents a strengthening of the fundamental basic research which will be of such crucial importance for the newly established medical imaging and visualization centre: MMIV.

Related links:

Publications

2020

    [PDF] [Bibtex]
    @article{RadEx,
    author = {Mörth, E. and Wagner-Larsen, K. and Hodneland, E. and Krakstad, C. and Haldorsen, I. S. and Bruckner, S. and Smit, N. N.},
    title = {RadEx: Integrated Visual Exploration of Multiparametric Studies for Radiomic Tumor Profiling},
    journal = {Accepted to appear at PacificGraphics and in an upcoming issue of Computer Graphics Forum},
    volume = {39},
    number = {7},
    year = {2020},
    abstract = {Better understanding of the complex processes driving tumor growth and metastases is critical for developing targeted treatment strategies in cancer. Radiomics extracts large amounts of features from medical images which enables radiomic tumor profiling in combination with clinical markers. However, analyzing complex imaging data in combination with clinical data is not trivial and supporting tools aiding in these exploratory analyses are presently missing. In this paper, we present an approach that aims to enable the analysis of multiparametric medical imaging data in combination with numerical, ordinal, and categorical clinical parameters to validate established and unravel novel biomarkers. We propose a hybrid approach where dimensionality reduction to a single axis is combined with multiple linked views allowing clinical experts to formulate hypotheses based on all available imaging data and clinical parameters. This may help to reveal novel tumor characteristics in relation to molecular targets for treatment, thus providing better tools for enabling more personalized targeted treatment strategies. To confirm the utility of our approach, we closely collaborate with experts from the field of gynecological cancer imaging and conducted an evaluation with six experts in this field.},
    pdf = "pdfs/Moerth-2020-RadEx.pdf",
    images = "images/Moerth-2020-RadEx.jpg",
    thumbnails = "images/Moerth-2020-RadEx-thumb.jpg",
    project = "ttmedvis",
    note = {Accepted for publication, to appear in an upcoming issue}
    }
    [PDF] [YT] [Bibtex]
    @INPROCEEDINGS{Moerth-2020-CGI,
    author = "Mörth, E. and Haldorsen, I.S. and Bruckner, S. and Smit, N.N.",
    title = "ParaGlyder: Probe-driven Interactive Visual Analysis for Multiparametric Medical Imaging Data",
    booktitle = "Accepted to appear at Computer Graphics International",
    year = "2020",
    abstract = "Multiparametric medical imaging describes approaches that include multiple imaging sequences acquired within the same imaging examination, as opposed to one single imaging sequence or imaging from multiple imaging modalities. Multiparametric imaging in cancer has been shown to be useful for tumor detection and may also depict functional tumor characteristics relevant for clinical phenotypes. However, when confronted with datasets consisting of multiple values per voxel, traditional reading of the imaging series fails to capture complicated patterns. Those patterns of potentially important imaging properties of the parameter space may be critical for the analysis. Standard approaches, such as transfer functions and juxtapositioned visualizations, fail to convey the shape of the multiparametric parameter distribution in sufficient detail. For these reasons, in this paper we present an approach that aims to enable the exploration and analysis of such multiparametric studies using an interactive visual analysis application to remedy the trade-offs between details in the value domain and in spatial resolution. Interactive probing within or across subjects allows for a digital biopsy that is able to uncover multiparametric tissue properties. This may aid in the discrimination between healthy and cancerous tissue, unravel radiomic tissue features that could be linked to targetable pathogenic mechanisms, and potentially highlight metastases that evolved from the primary tumor. We conducted an evaluation with eleven domain experts from the field of gynecological cancer imaging, neurological imaging, and machine learning research to confirm the utility of our approach.",
    note= "The final authenticated version is available online at https://doi.org/10.1007/978-3-030-61864-3_29",
    pdf = "pdfs/Moerth-2020-CGI-ParaGlyder.pdf",
    images = "images/Moerth-2020-ParaGlyder.PNG",
    thumbnails = "images/Moerth-2020-ParaGlyder-thumb.png",
    youtube = "https://youtu.be/S_M4CWXKz0U",
    publisher = "LNCS by Springer",
    project = "ttmedvis"
    }
    [PDF] [DOI] [Bibtex]
    @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 = {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"
    }

2019

    [DOI] [Bibtex]
    @article{kraima2019role,
    title={The role of the longitudinal muscle in the anal sphincter complex: Implications for the Intersphincteric Plane in Low Rectal Cancer Surgery?},
    author={Kraima, Anne C and West, Nicholas P and Roberts, Nicholas and Magee, Derek R and Smit, Noeska N and van de Velde, Cornelis JH and DeRuiter, Marco C and Rutten, Harm J and Quirke, Philip},
    journal={Clinical Anatomy},
    year={2019},
    doi="10.1002/ca.23444",
    url = "https://onlinelibrary.wiley.com/doi/full/10.1002/ca.23444",
    publisher={Wiley Online Library},
    project = "ttmedvis",
    images = {images/kraima-2019-role.png},
    thumbnails = {images/kraima-2019-role.png},
    abstract = {Intersphincteric resection (ISR) enables radical sphincter-preserving surgery in a subset of low rectal tumors impinging on the anal sphincter complex (ASC). Excellent anatomical knowledge is essential for optimal ISR. This study describes the role of the longitudinal muscle (LM) in the ASC and implications for ISR and other low rectal and anal pathologies. Six human adult en bloc cadaveric specimens (three males, three females) were obtained from the University of Leeds GIFT Research Tissue Programme. Paraffin-embedded mega blocks containing the ASC were produced and serially sectioned at 250?µm intervals. Whole mount microscopic sections were histologically stained and digitally scanned. The intersphincteric plane was shown to be potentially very variable. In some places adipose tissue is located between the external anal sphincter (EAS) and internal anal sphincter (IAS), whereas in others the LM interdigitates to obliterate the plane. Elsewhere the LM is (partly) absent with the intersphincteric plane lying on the IAS. The LM gave rise to the formation of the submucosae and corrugator ani muscles by penetrating the IAS and EAS. In four of six specimens, striated muscle fibers from the EAS curled around the distal IAS reaching the anal submucosa. The ASC formed a complex structure, varying between individuals with an inconstant LM affecting the potential location of the intersphincteric plane as well as a high degree of intermingling striated and smooth muscle fibers potentially further disrupting the plane. The complexity of identifying the correct pathological staging of low rectal cancer is also demonstrated.}
    }
    [DOI] [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,VIDI"
    }
    [DOI] [Bibtex]
    @article{Meuschke-2019-EvalViz,
    title = {EvalViz--Surface Visualization Evaluation Wizard for Depth and Shape Perception Tasks},
    author = {Meuschke, Monique and Smit, Noeska N and Lichtenberg, Nils and Preim, Bernhard and Lawonn, Kai},
    journal = {Computers \& Graphics},
    year = {2019},
    publisher = {Elsevier},
    number = "1",
    volume = "82",
    DOI = {10.1016/j.cag.2019.05.022},
    images = "images/Meuschke_EvalViz_2019.png",
    thumbnails = "images/Meuschke_EvalViz_2019.png",
    abstract = "User studies are indispensable for visualization application papers in order to assess the value and limitations of the presented approach. Important aspects are how well depth and shape information can be perceived, as coding of these aspects is essential to enable an understandable representation of complex 3D data. In practice, there is usually little time to perform such studies, and the establishment and conduction of user studies can be labour-intensive. In addition, it can be difficult to reach enough participants to obtain expressive results regarding the quality of different visualization techniques.
    In this paper, we propose a framework that allows visualization researchers to quickly create task-based user studies on depth and shape perception for different surface visualizations and perform the resulting tasks via a web interface. With our approach, the effort for generating user studies is reduced and at the same time the web-based component allows researchers to attract more participants to their study. We demonstrate our framework by applying shape and depth evaluation tasks to visualizations of various surface representations used in many technical and biomedical applications.",
    project = "ttmedvis"
    }
    [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"
    }

2018

    [PDF] [DOI] [YT] [Bibtex]
    @INPROCEEDINGS {Meuschke2018VCBM,
    author = "Monique Meuschke and Noeska N. Smit and Nils Lichtenberg and Bernhard Preim and Kai Lawonn",
    title = "Automatic Generation of Web-Based User Studies to Evaluate Depth Perception in Vascular Surface Visualizations",
    booktitle = "Proceedings of VCBM 2018",
    year = "2018",
    editor = "Anna Puig Puig and Thomas Schultz and Anna Vilanova and Ingrid Hotz and Barbora Kozlikova and Pere-Pau Vázquez",
    pages = "033-044",
    address = "Granada, Spain",
    publisher = "Eurographics Association",
    abstract = "User studies are often required in biomedical visualization application papers in order to provide evidence for the utility of the presented approach. An important aspect is how well depth information can be perceived, as depth encoding is important to enable an understandable representation of complex data.Unfortunately, in practice there is often little time available to perform such studies, and setting up and conducting user studies may be labor-intensive. In addition, it can be challenging to reach enough participants to support the contribution claims of the paper. In this paper, we propose a system that allows biomedical visualization researchers to quickly generate perceptual task-based user studies for novel surface visualizations, and to perform the resulting experiment via a web interface. This approach helps to reduce effort in the setup of user studies themselves, and at the same time leverages a web-based approach that can help researchers attract more participants to their study. We demonstrate our system using the specific application of depth judgment tasks to evaluate vascular surface visualizations, since there is a lot of recent interest in this area.However, the system is also generally applicable for conducting other task-baseduser studies in biomedical visualization.",
    pdf = "pdfs/meuschke2018VCBM.pdf",
    images = "images/vcbm2018.png",
    thumbnails = "images/vcbm2018.png",
    youtube = "https://www.youtube.com/watch?v=8lns8GGpPJI",
    crossref = "VCBM-proc",
    doi = "10.2312/vcbm.20181227",
    project = "ttmedvis"
    }
    [PDF] [YT] [Bibtex]
    @ARTICLE {lichtenbergsmithansenlawonn2018,
    author = "Nils Lichtenberg and Noeska Smit and Christian Hansen and Kai Lawonn",
    title = "Real-time field aligned stripe patterns",
    journal = "Computers & Graphics",
    year = "2018",
    volume = "74",
    pages = "137-149",
    month = "aug",
    abstract = "In this paper, we present a parameterization technique that can be applied to surface meshes in real-time without time-consuming preprocessing steps. The parameterization is suitable for the display of (un-)oriented patterns and texture patches, and to sample a surface in a periodic fashion. The method is inspired by existing work that solves a global optimization problem to generate a continuous stripe pattern on the surface, from which texture coordinates can be derived. We propose a local optimization approach that is suitable for parallel execution on the GPU, which drastically reduces computation time. With this, we achieve on-the-fly texturing of 3D, medium-sized (up to 70k vertices) surface meshes. The algorithm takes a tangent vector field as input and aligns the texture coordinates to it. Our technique achieves real-time parameterization of the surface meshes by employing a parallelizable local search algorithm that converges to a local minimum in a few iterations. The calculation in real-time allows for live parameter updates and determination of varying texture coordinates. Furthermore, the method can handle non-manifold meshes. The technique is useful in various applications, e.g., biomedical visualization and flow visualization. We highlight our method\s potential by providing usage scenarios for several applications.A PDF of the accepted manuscript is available via noeskasmit.com/wp-content/uploads/2018/08/lichtenberg_2018.pdf.",
    pdf = "pdfs/lichtenberg_2018.pdf",
    images = "images/Selection_384.png",
    thumbnails = "images/1-s2.0-S0097849318300591-fx1_lrg.jpg",
    youtube = "https://www.youtube.com/watch?v=7CpkHy8KPK8",
    project = "ttmedvis"
    }