Building-up and running a university-based research group is a multi-faceted undertaking. The visualization working group at TU Wien (vis-group) has been internationally active over more than 25 years. The group has been acting in a competitive scientific setting where sometimes contradicting multiple objectives require trade-offs and optimizations. Research-wise the group has been performing basic and applied research in visualization and visual computing. Teaching-wise the group has been involved in undergraduate and graduate lecturing in (medical) visualization and computer graphics. To be scientifically competitive requires to constantly expose the group and its members to a strong international competition at the highest level. This necessitates to shield the members against the ensuing pressures and demands and provide (emotional) support and encouragement. Internally, the vis-group has developed a unique professional and social interaction culture: work and celebrate, hard and together. This has crystallized into a nested, recursive, and triangular organization model, which concretizes what it takes to make a research group successful. The key elements are the creative and competent vis-group members who collaboratively strive for (scientific) excellence in a socially enjoyable environment.

Abstract Dental healthcare increasingly employs computer‐aided design software, to provide patients with high‐quality dental prosthetic devices. In modern dental reconstruction, dental technicians address the unique anatomy of each patient individually, by capturing the dental impression and measuring the mandibular movements. Subsequently, dental technicians design a custom denture that fits the patient from a functional point of view. The current Workflow does not include a systematic analysis of aesthetics, and dental technicians rely only on an aesthetically pleasing mock‐up that they discuss with the patient, and on their experience. Therefore, the final denture aesthetics remain unknown until the dental technicians incorporate the denture into the patient. In this Work, we present a solution that integrates aesthetics analysis into the functional Workflow of dental technicians. Our solution uses a video recording of the patient, to preview the denture design at any stage of the denture design process. We present a teeth pose estimation technique that enables denture preview and a set of linked visualizations that support dental technicians in the aesthetic design of dentures. These visualizations assist dental technicians in choosing the most aesthetically fitting preset from a library of dentures, in identifying the suitable denture size, and in adjusting the denture position. We demonstrate the utility of our system with four use cases, explored by a dental technician. Also, we performed a quantitative evaluation for teeth pose estimation, and an informal usability evaluation, with positive outcomes concerning the integration of aesthetics analysis into the functional Workflow.

Abstract Mathematical models of ordinary differential equations are used to describe and understand biological phenomena. These models are dynamical systems that often describe the time evolution of more than three variables, i.e., their dynamics take place in a multi‐dimensional space, called the phase space. Currently, mathematical domain scientists use plots of typical trajectories in the phase space to analyze the qualitative behavior of dynamical systems. These plots are called phase portraits and they perform well for 2D and 3D dynamical systems. However, for 4D, the visual exploration of trajectories becomes challenging, as simple subspace juxtaposition is not sufficient. We propose ManyLands to support mathematical domain scientists in analyzing 4D models of biological systems. By describing the subspaces as Lands, we accompany domain scientists along a continuous journey through 4D HyperLand, 3D SpaceLand, and 2D FlatLand, using seamless transitions. The Lands are also linked to 1D TimeLines. We offer an additional dissected view of trajectories that relies on small‐multiple compass‐alike pictograms for easy navigation across subspaces and trajectory segments of interest. We show three use cases of 4D dynamical systems from cell biology and biochemistry. An informal evaluation with mathematical experts confirmed that ManyLands helps them to visualize and analyze complex 4D dynamics, while facilitating mathematical experiments and simulations.

Abstract We present theBladder Runner, a novel tool to enable detailed visual exploration and analysis of the impact of bladder shape variation on the accuracy of dose delivery, during the course of prostate cancer radiotherapy (RT). Our tool enables the investigation of individual patients and cohorts through the entire treatment process, and it can give indications of RT‐induced complications for the patient. In prostate cancer RT treatment, despite the design of an initial plan prior to dose administration, bladder toxicity remains very common. The main reason is that the dose is delivered in multiple fractions over a period of weeks, during which, the anatomical variation of the bladder – due to differences in urinary filling – causes deviations between planned and delivered doses. Clinical researchers want to correlate bladder shape variations to dose deviations and toxicity risk through cohort studies, to understand which specific bladder shape characteristics are more prone to side effects. This is currently done with Dose‐Volume Histograms (DVHs), which provide limited, qualitative insight. The effect of bladder variation on dose delivery and the resulting toxicity cannot be currently examined with the DVHs. To address this need, we designed and implemented the Bladder Runner, which incorporates visualization strategies in a highly interactive environment with multiple linked views. Individual patients can be explored and analyzed through the entire treatment period, while inter‐patient and temporal exploration, analysis and comparison are also supported. We demonstrate the applicability of our presented tool with a usage scenario, employing a dataset of 29 patients followed through the course of the treatment, across 13 time points. We conducted an evaluation with three clinical researchers working on the investigation of RT‐induced bladder toxicity. All participants agreed that Bladder Runner provides better understanding and new opportunities for the exploration and analysis of the involved cohort data.

This work introduces a tool for interactive exploration and visualization using MetaTracts. MetaTracts is a novel method for extraction and visualization of individual fiber bundles and weaving patterns from X-ray computed tomography (XCT) scans of endless carbon fiber reinforced polymers (CFRPs). It is designed specifically to handle XCT scans of low resolutions where the individual fibers are barely visible, which makes extraction of fiber bundles a challenging problem. The proposed workflow is used to analyze unit cells of CFRP materials integrating a recurring weaving pattern. First, a coarse version of integral curves is used to trace sections of the individual fiber bundles in the woven CFRP materials. We call these sections MetaTracts. In the second step, these extracted fiber bundle sections are clustered using a two-step approach: first by orientation, then by proximity. The tool can generate volumetric representations as well as surface models of the extracted fiber bundles to be exported for further analysis. In addition a custom interactive tool for exploration and visual analysis of MetaTracts is designed. We evaluate the proposed workflow on a number of real world datasets and demonstrate that MetaTracts effectively and robustly identifies and extracts fiber bundles.

Abstract Material engineers use interrupted in situ tensile testing to investigate the damage mechanisms in composite materials. For each subsequent scan, the load is incrementally increased until the specimen is completely fractured. During the interrupted in situ testing of glass fiber reinforced polymers (GFRPs) defects of four types are expected to appear: matrix fracture, fiber/matrix debonding, fiber pull‐out, and fiber fracture. There is a growing demand for the detection and analysis of these defects among the material engineers. In this paper, we present a novel workflow for the detection, classification, and visual analysis of defects in GFRPs using interrupted in situ tensile tests in combination with X‐ray Computed Tomography. The workflow is based on the automatic extraction of defects and fibers. We introduce the automatic Defect Classifier assigning the most suitable type to each defect based on its geometrical features. We present a visual analysis system that integrates four visualization methods: 1) the Defect Viewer highlights defects with visually encoded type in the context of the original CT image, 2) the Defect Density Maps provide an overview of the defect distributions according to type in 2D and 3D, 3) the Final Fracture Surface estimates the material fracture's location and displays it as a 3D surface, 4) the 3D Magic Lens enables interactive exploration by combining detailed visualizations in the region of interest with overview visualizations as context. In collaboration with material engineers, we evaluate our solution and demonstrate its practical applicability.

This work introduces MetaTracts, a novel method for extracting and visualizing individual fiber bundles and weaving patterns from X-ray computed tomography (XCT) scans of endless carbon fiber reinforced polymers (CFRP). The proposed work flow is designed to analyze unit cells of CFRP materials integrating the recurring weaving pattern. It is designed to handle XCT scans of low resolution, in which individual fibers are not visible or are barely visible. First, a coarse version of integral curves is used to trace subsections of the individual fiber bundles in the woven CFRP materials. We call these sections MetaTracts. In the second step, these extracted fiber bundle sections (MetaTracts) are clustered using a two-step approach: first by orientation, then by proximity. The tool can generate volumetric representations as well as surface models of the extracted fiber bundles to be exported for further analysis. We evaluate the proposed work flow on a number of real world datasets and demonstrate that MetaTracts effectively and robustly identifies and separates different fiber bundles.

Advanced composites such as fiber reinforced polymers are promising candidate materials for future components as they allow integrating the continuously rising demands of industry regarding cost-effectiveness, function-orientation, integration and weight. The most important structures of fiber reinforced polymers are the individual fibers, as their characteristics (stiffness, strength, ductility, durability, etc.) to a large extent determine the properties of the final component. The main contribution of this paper is the introduction of a new system for interactive exploration and visual analysis of fiber properties in X-ray computed tomography data of fiber reinforced polymers. The presented tool uses parallel coordinates to define and configure initial fiber classes. Using a scatter plot matrix linked to the parallel coordinates the initial classification may be refined. This allows to analyze hidden relationships between individual fiber properties. 2D and 3D views depict the resulting fiber classifications. By using polar plots an intuitive rendering of the fiber orientation distribution is provided. In addition, two modules of higher abstraction are proposed: The Blob visualization creates a hull around fibers with similar characteristics. The fiber metadata visualization allows to calculate overlays for 2D and 3D views containing regional information of particular material characteristics. The proposed system has been evaluated by two groups of domain experts. Applying the presented concepts the user feedback shows that the domain experts are now able to efficiently perform tasks as classification of fibers, visualization of fiber lengths and orientations, and visualization of fiber regions. The insights gained can be forwarded to the design office as well as to material development and simulation, in order to speed up the development of novel composite components.

Abstract This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high‐resolution X‐ray computed tomography (XCT) for structural characterization and low‐resolution X‐ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non‐spatial information to provide insight into an industrial component's structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie‐chart glyphs show elemental composition in 2D slice‐views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie‐chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real‐world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided.

Multi-material components, which contain metal parts surrounded by plastic materials, are highly interesting for inspection using industrial 3D X-ray computed tomography (3DXCT). Examples of this application scenario are connectors or housings with metal inlays in the electronic or automotive industry. A major problem of this type of components is the presence of metal, which causes streaking artifacts and distorts the surrounding media in the reconstructed volume. Streaking artifacts and dark-band artifacts around metal components significantly influence the material characterization (especially for the plastic components). In specific cases these artifacts even prevent a further analysis. Due to the nature and the different characteristics of artifacts, the development of an efficient artifact-reduction technique in reconstruction-space is rather complicated. In this paper we present a projection-space pipeline for metal-artifacts reduction. The proposed technique first segments the metal in the spatial domain of the reconstructed volume in order to separate it from the other materials. Then metal parts are forward-projected on the set of projections in a way that metal-projection regions are treated as voids. Subsequently the voids, which are left by the removed metal, are interpolated in the 2D projections. Finally, the metal is inserted back into the reconstructed 3D volume during the fusion stage. We present a visual analysis tool, allowing for interactive parameter estimation of the metal segmentation. The results of the proposed artifact-reduction technique are demonstrated on a test part as well as on real world components. For these specimens we achieve a significant reduction of metal artifacts, allowing an enhanced material characterization.

Industrial cone-beam X-Ray computed tomography (CT) systems often face problems due to artifacts caused by a bad placement of the specimen on the rotary plate. This paper presents a visual-analysis tool for CT systems, which provides a simulation-based preview and estimates artifacts and deviations of a specimen's placement using the corresponding 3D geometrical surface model as input. The presented tool identifies potentially good or bad placements of a specimen and regions of a specimen, which cause the major portion of artefacts. The tool can be used for a preliminary analysis of the specimen before CT scanning, in order to determine the optimal way of placing the object. The analysis includes: penetration lengths, placement stability and an investigation in Radon space. Novel visualization techniques are applied to the simulation data. A stability widget is presented for determining the placement parameters' robustness. The performance and the comparison of results provided by the tool compared with real world data is demonstrated using two specimens.