Perceptually Uniform Construction of Illustrative Textures

Illustrative textures, such as stippling or hatching, were predominantly used as an alternative to conventional Phong rendering. Recently, the potential of encoding information on surfaces or maps using different densities has also been recognized. This has the significant advantage that additional color can be used as another visual channel and the illustrative textures can then be overlaid. Effectively, it is thus possible to display multiple information, such as two different scalar fields on surfaces simultaneously. In previous work, these textures were manually generated and the choice of density was unempirically determined. Here, we first want to determine and understand the perceptual space of illustrative textures. We chose a succession of simplices with increasing dimensions as primitives for our textures: Dots, lines, and triangles. Thus, we explore the texture types of stippling, hatching, and triangles. We create a range of textures by sampling the density space uniformly. Then, we conduct three perceptual studies in which the participants performed pairwise comparisons for each texture type. We use multidimensional scaling (MDS) to analyze the perceptual spaces per category. The perception of stippling and triangles seems relatively similar. Both are adequately described by a 1D manifold in 2D space. The perceptual space of hatching consists of two main clusters: Crosshatched textures, and textures with only one hatching direction. However, the perception of hatching textures with only one hatching direction is similar to the perception of stippling and triangles. Based on our findings, we construct perceptually uniform illustrative textures. Afterwards, we provide concrete application examples for the constructed textures.Comment: 11 pages, 15 figures, to be published in IEEE Transactions on Visualization and Computer Graphic

Expert exploranation for communicating scientific methods - A case study in conflict research

Science communication aims at making key research insights accessible to the broad public. If explanatory and exploratory visualization techniques are combined to do so, the approach is also referred to as exploranation. In this context, the audience is usually not required to have domain expertise. However, we show that exploranation can not only support the communication between researchers and a broad audience, but also between researchers directly. With the goal of communicating an existing method for conducting causal inference on spatio-temporal conflict event data, we investigated how to perform exploranation for experts, i.e., expert exploranation. Based on application scenarios of the inference method, we developed three versions of an interactive visual story to explain the method to conflict researchers. We abstracted the corresponding design process and evaluated the stories both with experts who were unfamiliar with the explained method and experts who were already familiar with it. The positive and extensive feedback from the evaluation shows that expert exploranation is a promising direction for visual storytelling, as it can help to improve scientific outreach, methodological understanding, and accessibility for researchers new to a field

Longitudinal wall shear stress evaluation using centerline projection approach in the numerical simulations of the patient-based carotid artery

In this numerical study areas of the carotid bifurcation and of a distal stenosis in the internal carotid artery are closely observed to evaluate the patient's current risks of ischemic stroke. An indicator for the vessel wall defects is the stress the blood is exerting on the surrounding vessel tissue, expressed standardly by the amplitude of the wall shear stress vector (WSS) and its oscillatory shear index. In contrast, our orientation-based shear evaluation detects negative shear stresses corresponding with reversal flow appearing in low shear areas. In our investigations of longitudinal component of the wall shear vector, tangential vectors aligned longitudinally with the vessel are necessary. However, as a result of stenosed regions and imaging segmentation techniques from patients' CTA scans, the geometry model's mesh is non-smooth on its surface areas and the automatically generated tangential vector field is discontinuous and multi-directional, making an interpretation of the orientation-based risk indicators unreliable. We improve the evaluation of longitudinal shear stress by applying the projection of the vessel's center-line to the surface to construct smooth tangetial field aligned longitudinaly with the vessel. We validate our approach for the longitudinal WSS component and the corresponding oscillatory index by comparing them to results obtained using automatically generated tangents in both rigid and elastic vessel modeling as well as to amplitude based indicators. The major benefit of our WSS evaluation based on its longitudinal component for the cardiovascular risk assessment is the detection of negative WSS indicating persitent reversal flow. This is impossible in the case of the amplitude-based WSS

Longitudinal visualization for exploratory analysis of multiple sclerosis lesions

In multiple sclerosis (MS), the amount of brain damage, anatomical location, shape, and changes are important aspects that help medical researchers and clinicians to understand the temporal patterns of the disease. Interactive visualization for longitudinal MS data can support studies aimed at exploratory analysis of lesion and healthy tissue topology. Existing visualizations in this context comprise bar charts and summary measures, such as absolute numbers and volumes to summarize lesion trajectories over time, as well as summary measures such as volume changes. These techniques can work well for datasets having dual time point comparisons. For frequent follow-up scans, understanding patterns from multimodal data is difficult without suitable visualization approaches. As a solution, we propose a visualization application, wherein we present lesion exploration tools through interactive visualizations that are suitable for large time-series data. In addition to various volumetric and temporal exploration facilities, we include an interactive stacked area graph with other integrated features that enable comparison of lesion features, such as intensity or volume change. We derive the input data for the longitudinal visualizations from automated lesion tracking. For cases with a larger number of follow-ups, our visualization design can provide useful summary information while allowing medical researchers and clinicians to study features at lower granularities. We demonstrate the utility of our visualization on simulated datasets through an evaluation with domain experts.publishedVersio

Keynote: Visualization in the Wild

Inhalt: Was ist eigentlich Visualisierung?; Wozu Visualisierun?; Komplexere Beispiele; Manipulierende Visualisierung?; Farbwahl überdenken?; Effekte der Visualisierung; Motivation; Stile; Resultate; Ergebnis; Frangi Filter; Sortierung der Ritzungen; Generierung von Ritzungen; Ergebnisse; Motivation; Morphologische Parameter; Robusthei

VEHICLE: Validation and exploration of the hierarchical integration of conflict event data

The exploration of large-scale conflicts, as well as their causes and effects, is an important aspect of socio-political analysis. Since event data related to major conflicts are usually obtained from different sources, researchers developed a semi-automatic matching algorithm to integrate event data of different origins into one comprehensive dataset using hierarchical taxonomies. The validity of the corresponding integration results is not easy to assess since the results depend on user-defined input parameters and the relationships between the original data sources. However, only rudimentary visualization techniques have been used so far to analyze the results, allowing no trustworthy validation or exploration of how the final dataset is composed. To overcome this problem, we developed VEHICLE, a web-based tool to validate and explore the results of the hierarchical integration. For the design, we collaborated with a domain expert to identify the underlying domain problems and derive a task and workflow description. The tool combines both traditional and novel visual analysis techniques, employing statistical and map-based depictions as well as advanced interaction techniques. We showed the usefulness of VEHICLE in two case studies and by conducting an evaluation together with conflict researchers, confirming domain hypotheses and generating new insights