Browsing by Author "Baum, Daniel"

Now showing 1 - 7 of 7
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    Automatic Segmentation of Tooth Images: Optimization of Multi-parameter Image Processing Workflow
    (The Eurographics Association, 2022) Bressan Fogalli, Giovani; Line, Sérgio Roberto Peres; Baum, Daniel; Krone, Michael; Lenti, Simone; Schmidt, Johanna
    The development of specific algorithms in image processing are usually related to dataset characteristics. Those characteristics will influence the number of instructions required to solve a problem. Normally, the more complex a set of instructions is, the more parameters need to be set. Dealing with such degrees of freedom, sometimes leading to subjective decision making, is time-consuming and frequently leads to errors or sub-optimal results of the developed model. Here, we deal with a model for segmentation of masks of tooth images containing a pattern of bands called Hunter-Schreger Bands (HSB). They appear on tooth surface when lit from the side. This segmentation process is only one step of a pipeline whose overall goal is human biometric identification to be used, e.g., in forensics. The segmentation algorithm, which exploits the anisotropy of the image, uses several parameters and choosing the optimal combination of them is challenging. The aim of this work was to utilize visual data analysis tools to optimize the chosen parameters and to understand their influence on the performance of the algorithm. Our results reveal that a slightly better combination of parameter values can be found starting from the experimentally determined initial parameters. This approach can be repeatedly performed to achieve even better parameterizations. To more deeply understand the influence of the parameters on the final result, more sophisticated visual interaction tools will be explored in future work.
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    Global and Local Mesh Morphing for Complex Biological Objects from µCT Data
    (The Eurographics Association, 2018) Knötel, David; Becker, Carola; Scholtz, Gerhard; Baum, Daniel; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
    We show how biologically coherent mesh models of animals can be created from µCT data to generate artificial yet naturally looking intermediate objects. The whole pipeline of processing algorithms is presented, starting from generating topologically equivalent surface meshes, followed by solving the correspondence problem, and, finally, creating a surface morphing. In this pipeline, we address all the challenges that are due to dealing with complex biological, non-isometric objects. For biological objects it is often particularly important to obtain deformations that look as realistic as possible. In addition, spatially non-uniform shape morphings that only change one part of the surface and keep the rest as stable as possible are of interest for evolutionary studies, since functional modules often change independently from one another. We use Poisson interpolation for this purpose and show that it is well suited to generate both global and local shape deformations.
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    An Interactive Approach for Identifying Structure Definitions
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Mikula, Natalia; Dörffel, Tom; Baum, Daniel; Hege, Hans-Christian; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Our ability to grasp and understand complex phenomena is essentially based on recognizing structures and relating these to each other. For example, any meteorological description of a weather condition and explanation of its evolution recurs to meteorological structures, such as convection and circulation structures, cloud fields and rain fronts. All of these are spatiotemporal structures, defined by time-dependent patterns in the underlying fields. Typically, such a structure is defined by a verbal description that corresponds to the more or less uniform, often somewhat vague mental images of the experts. However, a precise, formal definition of the structures or, more generally, of the concepts is often desirable, e.g., to enable automated data analysis or the development of phenomenological models. Here, we present a systematic approach and an interactive tool to obtain formal definitions of spatiotemporal structures. The tool enables experts to evaluate and compare different structure definitions on the basis of data sets with time-dependent fields that contain the respective structure. Since structure definitions are typically parameterized, an essential part is to identify parameter ranges that lead to desired structures in all time steps. In addition, it is important to allow a quantitative assessment of the resulting structures simultaneously. We demonstrate the use of the tool by applying it to two meteorological examples: finding structure definitions for vortex cores and center lines of temporarily evolving tropical cyclones. Ideally, structure definitions should be objective and applicable to as many data sets as possible. However, finding such definitions, e.g., for the common atmospheric structures in meteorology, can only be a long-term goal. The proposed procedure, together with the presented tool, is just a first systematic approach aiming at facilitating this long and arduous way.
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    Polyp-Cavity Segmentation of Cold-Water Corals guided by Ambient Occlusion and Ambient Curvature
    (The Eurographics Association, 2022) Schmitt, Kira; Titschack, Jürgen; Baum, Daniel; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
    The segmentation of cavities in three-dimensional images of arbitrary objects is a difficult problem since the cavities are usually connected to the outside of the object without any difference in image intensity. Hence, the information whether a voxel belongs to a cavity or the outside needs to be derived from the ambient space. If a voxel is enclosed by object material, it is very likely that this voxel belongs to a cavity. However, there are dense structures where a voxel might still belong to the outside even though it is surrounded to a large degree by the object. This is, for example, the case for coral colonies. Therefore, additional information needs to be considered to distinguish between those cases. In this paper, we introduce the notion of ambient curvature, present an efficient way to compute it, and use it to segment coral polyp cavities by integrating it into the ambient occlusion framework. Moreover, we combine the ambient curvature with other ambient information in a Gaussian mixture model, trained from a few user scribbles, resulting in a significantly improved cavity segmentation. We showcase the superiority of our approach using four coral colonies of very different morphological types. While in this paper we restrict ourselves to coral data, we believe that the concept of ambient curvature is also useful for other data. Furthermore, our approach is not restricted to curvature but can be easily extended to exploit any properties given on an object's surface, thereby adjusting it to specific applications.
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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.