DSpace Repository :: Browsing by Author "Scheuermann, Gerik"

Browsing by Author "Scheuermann, Gerik"

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Automatic Improvement of Continuous Colormaps in Euclidean Colorspaces
(The Eurographics Association and John Wiley & Sons Ltd., 2021) Nardini, Pascal; Chen, Min; Böttinger, Michael; Scheuermann, Gerik; Bujack, Roxana; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
Colormapping is one of the simplest and most widely used data visualization methods within and outside the visualization community. Uniformity, order, discriminative power, and smoothness of continuous colormaps are the most important criteria for evaluating and potentially improving colormaps. We present a local and a global automatic optimization algorithm in Euclidean color spaces for each of these design rules in this work. As a foundation for our optimization algorithms, we used the CCC-Tool colormap specification (CMS); each algorithm has been implemented in this tool. In addition to synthetic examples that demonstrate each method's effect, we show the outcome of some of the methods applied to a typhoon simulation.
Fiber Surfaces for many Variables
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Blecha, Christian; Raith, Felix; Präger, Arne Jonas; Nagel, Thomas; Kolditz, Olaf; Maßmann, Jobst; Röber, Niklas; Böttinger, Michael; Scheuermann, Gerik; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
Scientific visualization deals with increasingly complex data consisting of multiple fields. Typical disciplines generating multivariate data are fluid dynamics, structural mechanics, geology, bioengineering, and climate research. Quite often, scientists are interested in the relation between some of these variables. A popular visualization technique for a single scalar field is the extraction and rendering of isosurfaces. With this technique, the domain can be split into two parts, i.e. a volume with higher values and one with lower values than the selected isovalue. Fiber surfaces generalize this concept to two or three scalar variables up to now. This article extends the notion further to potentially any finite number of scalar fields. We generalize the fiber surface extraction algorithm of Raith et al. [RBN*19] from 3 to d dimensions and demonstrate the technique using two examples from geology and climate research. The first application concerns a generic model of a nuclear waste repository and the second one an atmospheric simulation over central Europe. Both require complex simulations which involve multiple physical processes. In both cases, the new extended fiber surfaces helps us finding regions of interest like the nuclear waste repository or the power supply of a storm due to their characteristic properties.
Towards Closing the Gap of Medical Visualization Research and Clinical Daily Routine
(The Eurographics Association, 2020) Maack, Robin Georg Claus; Saur, Dorothee; Hagen, Hans; Scheuermann, Gerik; Gillman, Christina; Gillmann, Christina and Krone, Michael and Reina, Guido and Wischgoll, Thomas
Medical visualization papers are constantly published throughout the last years, but many never make their way into clinical daily routine. In this manuscript we aim to examine the gap between visualization research and clinical daily routine and suggest a mechanism that can lead towards closing this gap. We first identify the actors involved in developing new medical visualization approaches and their different views in this process. Then we develop a software development process unifying all actors and their needs. In addition, we collect further barriers in the medical software development process.
Uncertainty-aware Brain Lesion Visualization
(The Eurographics Association, 2020) Gillmann, Christina; Saur, Dorothee; Wischgoll, Thomas; Hoffmann, Karl-Titus; Hagen, Hans; Maciejewski, Ross; Scheuermann, Gerik; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
A brain lesion is an area of tissue that has been damaged through injury or disease. Its analysis is an essential task for medical researchers to understand diseases and find proper treatments. In this context, visualization approaches became an important tool to locate, quantify, and analyze brain lesions. Unfortunately, image uncertainty highly effects the accuracy of the visualization output. These effects are not covered well in existing approaches, leading to miss-interpretation or a lack of trust in the analysis result. In this work, we present an uncertainty-aware visualization pipeline especially designed for brain lesions. Our method is based on an uncertainty measure for image data that forms the input of an uncertainty-aware segmentation approach. Here, medical doctors can determine the lesion in the patient's brain and the result can be visualized by an uncertainty-aware geometry rendering. We applied our approach to two patient datasets to review the lesions. Our results indicate increased knowledge discovery in brain lesion analysis that provides a quantification of trust in the generated results.
Uncertainty-aware Detection and Visualization of Ocean Eddies in Ensemble Flow Fields - A Case Study of the Red Sea
(The Eurographics Association, 2021) Raith, Felix; Scheuermann, Gerik; Gillmann, Christina; Dutta, Soumya and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirk
Eddy detection is a state of the art tool to examine transport behavior in oceans, as they form circular movements that are highly involved in transferring mass in an ocean. To achieve this, ocean simulations are run multiple times, and an eddy detection is performed in the final simulation results. Unfortunately, this process is affected by a variety of uncertainties. In this manuscript, we aim to identify the types of uncertainty inherent in ocean simulations. For each of the identified uncertainties, we provide a quantification approach. Based on the quantified uncertainties, we provide a visualization approach that consists of domain embedded views and an uncertainty space view connected via interaction. We showed the effectiveness of our approach by performed a case study of the Red Sea.
Uncertainty-aware Visualization in Medical Imaging - A Survey
(The Eurographics Association and John Wiley & Sons Ltd., 2021) Gillmann, Christina; Saur, Dorothee; Wischgoll, Thomas; Scheuermann, Gerik; Smit, Noeska and Vrotsou, Katerina and Wang, Bei
Medical imaging (image acquisition, image transformation, and image visualization) is a standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students. Each of these steps is affected by uncertainty, which can highly influence the decision-making process of clinicians. Visualization can help in understanding and communicating these uncertainties. In this manuscript, we aim to summarize the current state-of-the-art in uncertainty-aware visualization in medical imaging. Our report is based on the steps involved in medical imaging as well as its applications. Requirements are formulated to examine the considered approaches. In addition, this manuscript shows which approaches can be combined to form uncertainty-aware medical imaging pipelines. Based on our analysis, we are able to point to open problems in uncertainty-aware medical imaging.
Understanding Graph Convolutional Networks to detect Brain Lesions from Stroke
(The Eurographics Association, 2022) Iporre-Rivas, Ariel; Scheuermann, Gerik; Gillmann, Christina; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
Brain lesions derived from stroke episodes can result in disabilities for a patient. Therefore, the segmentation of brain lesions is an important task in neurology. Recently this task has been mainly tackled by machine learning approaches that demonstrated to be very successful. One of these approaches is Graph Convolutional Networks (GCN), where the input image is interpreted as a graph structure. As usual for neural networks, the interpretability is hard due to their black-box nature. We provide an interactive visualization of the activation inherent in the GCN, which is map from the original dataset. We visualize the activation values of the underlying graph network on top of the input image. We show the usability of our approach by applying it to a GCN that was trained on a real-world dataset.
Visual Analysis of a Full-Scale-Emplacement Experiment in the Underground Rock Laboratory Mont Terri using Fiber Surfaces
(The Eurographics Association, 2020) Raith, Felix; Blecha, Christian; Rink, Karsten; Wang, Wenqing; Kolditz, Olaf; Shao, Hua; Scheuermann, Gerik; Dutta, Soumya and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirk
In the Underground Rock Laboratory Mont Terri, research has been conducted for over 20 years into the storage of radioactive waste in Opalinus Clay. The fitness for such storage depends on the prevailing geological material. Experiments and multiphysics simulations investigate the long-term changes in the Opalinus Clay. The resulting data are highly multivariate, and environmental scientists visually analyze the data using predefined color lookup tables. The fiber surfaces of Raith et al. offer the researchers a new approach for visual analysis. However, the existing algorithm for the calculation is subject to certain limitations due to special cases that lead to no or incomplete fiber surfaces. In this paper, we improve the fiber surface algorithm of Raith et al., which reduces numerical errors and accelerates the existing algorithm. This improvement also makes it possible that the interactor no longer needs to be closed and convex. We then use the Full-Scale Emplacement Experiment to show how the improved algorithm can help in the visual analysis of multivariate data.
Visual Analysis of the Relation Between Stiffness Tensor and the Cauchy-Green Tensor
(The Eurographics Association, 2021) Blecha, Christian; Hergl, Chiara; Nagel, Thomas; Scheuermann, Gerik; Agus, Marco and Garth, Christoph and Kerren, Andreas
Stress and strain tensors, two well-known quantities in mechanical engineering, are linked through a fourth-order stiffness tensor, which is not considered by many visualizations due to its complexity. Considering an orthotropic material, the tensor naturally decomposes into nine known material properties.We used fiber surfaces to analyze a data set representing a biological tissue. A sphere is pushed into the material to confirm the mathematical link as well as the possibility to extract highly deformed regions even if only the stiffness tensor is available.
Visualization Framework for Assisting Interface Optimization of Hybrid Component Design
(The Eurographics Association, 2020) Kretzschmar, Vanessa; Gillmann, Christina; Günther, Fabian; Stommel, Markus; Scheuermann, Gerik; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
Reliable component design is one of structural mechanics' main objectives. Especially for lightweight constructions, hybrid parts made of a multi-material combination are used. The design process for these parts often becomes very challenging. The critical section of such hybrid parts is usually the interface layer that often builds the weakest zone. In this paper, we study a hybrid part made of metal and carbon fiber-reinforced composite, where the metal insert is coated by a thermoplastic to decrease the jump in stiffness between the two primary structural materials. To prevent stress peaks in small volumes of the part , mechanical engineers aim to design functional elements at the thermoplastic interface, to homogenize the stress distribution. The placement of such load transmitting functional elements at the thermoplastics interface has a crucial impact on the overall stability and mechanical performance of the design. Resulting from this, mechanical engineers acquire large amounts of simulations outputting multi-field datasets, to examine the impact of differently designed load transmitting elements, their number, and positioning in the interface between metal and composite. In order to assist mechanical engineers in deeper exploration of the often numerous set of simulations, a framework based on visual analytics techniques was developed in close collaboration with engineers. To match their needs, a requirement analysis was performed, and visualizations were discussed steadily. We show how the presented framework helps engineers gaining novel insights to optimize the hybrid component based on the selected load transmitting elements.
Visualization of Tensor Fields in Mechanics
(© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Hergl, Chiara; Blecha, Christian; Kretzschmar, Vanessa; Raith, Felix; Günther, Fabian; Stommel, Markus; Jankowai, Jochen; Hotz, Ingrid; Nagel, Thomas; Scheuermann, Gerik; Benes, Bedrich and Hauser, Helwig
Tensors are used to describe complex physical processes in many applications. Examples include the distribution of stresses in technical materials, acting forces during seismic events, or remodeling of biological tissues. While tensors encode such complex information mathematically precisely, the semantic interpretation of a tensor is challenging. Visualization can be beneficial here and is frequently used by domain experts. Typical strategies include the use of glyphs, color plots, lines, and isosurfaces. However, data complexity is nowadays accompanied by the sheer amount of data produced by large‐scale simulations and adds another level of obstruction between user and data. Given the limitations of traditional methods, and the extra cognitive effort of simple methods, more advanced tensor field visualization approaches have been the focus of this work. This survey aims to provide an overview of recent research results with a strong application‐oriented focus, targeting applications based on continuum mechanics, namely the fields of structural, bio‐, and geomechanics. As such, the survey is complementing and extending previously published surveys. Its utility is twofold: (i) It serves as basis for the visualization community to get an overview of recent visualization techniques. (ii) It emphasizes and explains the necessity for further research for visualizations in this context.

Browsing by Author "Scheuermann, Gerik"

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