36-Issue 3

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https://diglib.eg.org/handle/10.2312/2631433

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Browsing 36-Issue 3 by Subject "Applications"

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    Glyph-Based Comparative Stress Tensor Visualization in Cerebral Aneurysms
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Meuschke, Monique; Voß, Samuel; Beuing, Oliver; Preim, Bernhard; Lawonn, Kai; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    We present the first visualization tool that enables a comparative depiction of structural stress tensor data for vessel walls of cerebral aneurysms. Such aneurysms bear the risk of rupture, whereas their treatment also carries considerable risks for the patient. Medical researchers emphasize the importance of analyzing the interaction of morphological and hemodynamic information for the patient-specific rupture risk evaluation and treatment analysis. Tensor data such as the stress inside the aneurysm walls characterizes the interplay between the morphology and blood flow and seems to be an important rupture-prone criterion. We use different glyph-based techniques to depict local stress tensors simultaneously and compare their applicability to cerebral aneurysms in a user study. We thus offer medical researchers an effective visual exploration tool to assess the aneurysm rupture risk.We developed a GPU-based implementation of our techniques with a flexible interactive data exploration mechanism. Our depictions are designed in collaboration with domain experts, and we provide details about the evaluation.
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    Illustrative Visualization of Mesoscale Ocean Eddies
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Liu, Li; Silver, Deborah; Bemis, Karen; Kang, Dujuan; Curchitser, Enrique; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Feature-based time-varying volume visualization is combined with illustrative visualization to tell the story of how mesoscale ocean eddies form in the Gulf Stream and transport heat and nutrients across the ocean basin. The internal structure of these three-dimensional eddies and the kinematics with which they move are critical to a full understanding of ocean eddies. In this work, we apply a feature-based method to track instances of ocean eddies through the time steps of a high-resolution multidecadal regional ocean model and generate a series of eddy paths which reflect the life cycle of individual eddy instances. Based on the computed metadata, several important geometric and physical properties of eddy are computed. Illustrative visualization techniques, including visual effectiveness enhancement, focus+context, and smart visibility, are combined with the extracted volume features to explore eddy characteristics at different levels. An evaluation by domain experts indicates that combining our feature-based techniques with illustrative visualization techniques provides an insight into the role eddies play in ocean circulation. The domain experts expressed a preference for our methods over existing tools.
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    Overview + Detail Visualization for Ensembles of Diffusion Tensors
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Zhang, Changgong; Caan, Matthan W. A.; Höllt, Thomas; Eisemann, Elmar; Vilanova, Anna; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    A Diffusion Tensor Imaging (DTI) group study consists of a collection of volumetric diffusion tensor datasets (i.e., an ensemble) acquired from a group of subjects. The multivariate nature of the diffusion tensor imposes challenges on the analysis and the visualization. These challenges are commonly tackled by reducing the diffusion tensors to scalar-valued quantities that can be analyzed with common statistical tools. However, reducing tensors to scalars poses the risk of losing intrinsic information about the tensor. Visualization of tensor ensemble data without loss of information is still a largely unsolved problem. In this work, we propose an overview + detail visualization to facilitate the tensor ensemble exploration. We define an ensemble representative tensor and variations in terms of the three intrinsic tensor properties (i.e., scale, shape, and orientation) separately. The ensemble summary information is visually encoded into the newly designed aggregate tensor glyph which, in a spatial layout, functions as the overview. The aggregate tensor glyph guides the analyst to interesting areas that would need further detailed inspection. The detail views reveal the original information that is lost during aggregation. It helps the analyst to further understand the sources of variation and formulate hypotheses. To illustrate the applicability of our prototype, we compare with most relevant previous work through a user study and we present a case study on the analysis of a brain diffusion tensor dataset ensemble from healthy volunteers.
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    Visual Verification of Cancer Staging for Therapy Decision Support
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Cypko, Mario A.; Wojdziak, Jan; Stoehr, Matthaeus; Kirchner, Bettina; Preim, Bernhard; Dietz, Andreas; Lemke, Heinz U.; Oeltze-Jafra, Steffen; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    It is generally accepted practice that each cancer patient case should be discussed in a clinical expert meeting, the so-called tumor board. A central role in finding the best therapy options for patients with solid tumors plays the Tumor, lymph Node, and Metastasis staging (TNM staging). Correctness of TNM staging has a significant impact on the therapy choice and hence on the patient's post-therapeutic quality of life or even survival. If inconsistencies in the TNM staging occur, possible explanations and solutions must be found based on the complex patient records, which takes the costly time of (multiple) physicians. We propose a more efficient visual analysis component, which supports a physician in verifying the given TNM staging before forwarding it to the tumor board. Our component comprises a Bayesian network model of the TNM staging process. Using information from the patient records and Bayesian inference, the models computes a patient-specific TNM staging, which is then explored and compared to the given staging by means of a graph-based visualization. Our component is implemented in a research prototype that supports an understanding of the model computations, allows for a fast identification of important influencing factors, and facilitates a quick detection of differences between two TNM stagings. We evaluated our component with five physicians, each studying 20 cases of laryngeal cancer.
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    Visualizing Probabilistic Multi-Phase Fluid Simulation Data using a Sampling Approach
    (The Eurographics Association and John Wiley & Sons Ltd., 2017) Hummel, Mathias; Jöckel, Lisa; Schäfer, Jan; Hlawitschka, Mark Werner; Garth, Christoph; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
    Eulerian Method of Moment (MoM) solvers are gaining popularity for multi-phase CFD simulation involving bubbles or droplets in process engineering. Because the actual positions of bubbles are uncertain, the spatial distribution of bubbles is described by scalar fields of moments, which can be interpreted as probability density functions. Visualizing these simulation results and comparing them to physical experiments is challenging, because neither the shape nor the distribution of bubbles described by the moments lend themselves to visual interpretation. In this work, we describe a visualization approach that provides explicit instances of the bubble distribution and produces bubble geometry based on local flow properties. To facilitate animation, the instancing of the bubble distribution provides coherence over time by advancing bubbles between time steps and updating the distribution. Our approach provides an intuitive visualization and enables direct visual comparison of simulation results to physical experiments.