Browsing by Author "Hege, Hans-Christian"

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    Rapid Prototyping for Coordinated Views of Multi-scale Spatial and Abstract Data: A Grammar-based Approach
    (The Eurographics Association, 2023) Harth, Philipp; Bast, Arco; Troidl, Jakob; Meulemeester, Bjorge; Pfister, Hanspeter; Beyer, Johanna; Oberlaender, Marcel; Hege, Hans-Christian; Baum, Daniel; Hansen, Christian; Procter, James; Renata G. Raidou; Jönsson, Daniel; Höllt, Thomas
    Visualization grammars are gaining popularity as they allow visualization specialists and experienced users to quickly create static and interactive views. Existing grammars, however, mostly focus on abstract views, ignoring three-dimensional (3D) views, which are very important in fields such as natural sciences. We propose a generalized interaction grammar for the problem of coordinating heterogeneous view types, such as standard charts (e.g., based on Vega-Lite) and 3D anatomical views. An important aspect of our web-based framework is that user interactions with data items at various levels of detail can be systematically integrated and used to control the overall layout of the application workspace. With the help of a concise JSON-based specification of the intended workflow, we can handle complex interactive visual analysis scenarios. This enables rapid prototyping and iterative refinement of the visual analysis tool in collaboration with domain experts. We illustrate the usefulness of our framework in two real-world case studies from the field of neuroscience. Since the logic of the presented grammar-based approach for handling interactions between heterogeneous web-based views is free of any application specifics, it can also serve as a template for applications beyond biological research.
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    A Stratification Matrix Viewer for Analysis of Neural Network Data
    (The Eurographics Association, 2022) Harth, Philipp; Vohra, Sumit; Udvary, Daniel; Oberlaender, Marcel; Hege, Hans-Christian; Baum, Daniel; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
    The analysis of brain networks is central to neurobiological research. In this context the following tasks often arise: (1) understand the cellular composition of a reconstructed neural tissue volume to determine the nodes of the brain network; (2) quantify connectivity features statistically; and (3) compare these to predictions of mathematical models. We present a framework for interactive, visually supported accomplishment of these tasks. Its central component, the stratification matrix viewer, allows users to visualize the distribution of cellular and/or connectional properties of neurons at different levels of aggregation. We demonstrate its use in four case studies analyzing neural network data from the rat barrel cortex and human temporal cortex.
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    Thin-Volume Visualization on Curved Domains
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Herter, Felix; Hege, Hans-Christian; Hadwiger, Markus; Lepper, Verena; Baum, Daniel; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Thin, curved structures occur in many volumetric datasets. Their analysis using classical volume rendering is difficult because parts of such structures can bend away or hide behind occluding elements. This problem cannot be fully compensated by effective navigation alone, as structure-adapted navigation in the volume is cumbersome and only parts of the structure are visible in each view. We solve this problem by rendering a spatially transformed view of the volume so that an unobstructed visualization of the entire curved structure is obtained. As a result, simple and intuitive navigation becomes possible. The domain of the spatial transform is defined by a triangle mesh that is topologically equivalent to an open disc and that approximates the structure of interest. The rendering is based on ray-casting, in which the rays traverse the original volume. In order to carve out volumes of varying thicknesses, the lengths of the rays as well as the positions of the mesh vertices can be easily modified by interactive painting under view control. We describe a prototypical implementation and demonstrate the interactive visual inspection of complex structures from digital humanities, biology, medicine, and material sciences. The visual representation of the structure as a whole allows for easy inspection of interesting substructures in their original spatial context. Overall, we show that thin, curved structures in volumetric data can be excellently visualized using ray-casting-based volume rendering of transformed views defined by guiding surface meshes, supplemented by interactive, local modifications of ray lengths and vertex positions.
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    A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Fröhler, Bernhard; Elberfeld, Tim; Möller, Torsten; Hege, Hans-Christian; Weissenböck, Johannes; De Beenhouwer, Jan; Sijbers, Jan; Kastner, Johann; Heinzl, Christoph; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    We present visual analysis methods for the evaluation of tomographic fiber reconstruction algorithms by means of analysis, visual debugging and comparison of reconstructed fibers in materials science. The methods are integrated in a tool (FIAKER) that supports the entire workflow. It enables the analysis of various fiber reconstruction algorithms, of differently parameterized fiber reconstruction algorithms and of individual steps in iterative fiber reconstruction algorithms. Insight into the performance of fiber reconstruction algorithms is obtained by a list-based ranking interface. A 3D view offers interactive visualization techniques to gain deeper insight, e.g., into the aggregated quality of the examined fiber reconstruction algorithms and parameterizations. The tool was designed in close collaboration with researchers who work with fiber-reinforced polymers on a daily basis and develop algorithms for tomographic reconstruction and characterization of such materials. We evaluate the tool using synthetic datasets as well as tomograms of real materials. Five case studies certify the usefulness of the tool, showing that it significantly accelerates the analysis and provides valuable insights that make it possible to improve the fiber reconstruction algorithms. The main contribution of the paper is the well-considered combination of methods and their seamless integration into a visual tool that supports the entire workflow. Further findings result from the analysis of (dis-)similarity measures for fibers as well as from the discussion of design decisions. It is also shown that the generality of the analytical methods allows a wider range of applications, such as the application in pore space analysis.