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During the last decades, anatomy has become an interesting topic in education—even for laymen or schoolchildren. As medical imaging techniques become increasingly sophisticated, virtual anatomical education applications have emerged. Still, anatomical models are often preferred, as they facilitate 3D localization of anatomical structures. Recently, data physicalizations (i.e., physical visualizations) have proven to be effective and engaging—sometimes, even more than their virtual counterparts. So far, medical data physicalizations involve mainly 3D printing, which is still expensive and cumbersome. We investigate alternative forms of physicalizations, which use readily available technologies (home printers) and inexpensive materials (paper or semi‐transparent films) to generate crafts for anatomical edutainment. To the best of our knowledge, this is the first computer‐generated crafting approach within an anatomical edutainment context. Our approach follows a cost‐effective, simple, and easy‐to‐employ workflow, resulting in assemblable data sculptures (i.e., semi‐transparent sliceforms). It primarily supports volumetric data (such as CT or MRI), but mesh data can also be imported. An octree slices the imported volume and an optimization step simplifies the slice configuration, proposing the optimal order for easy assembly. A packing algorithm places the resulting slices with their labels, annotations, and assembly instructions on a paper or transparent film of user‐selected size, to be printed, assembled into a sliceform, and explored. We conducted two user studies to assess our approach, demonstrating that it is an initial positive step towards the successful creation of interactive and engaging anatomical physicalizations. [ABSTRACT FROM AUTHOR]

Reconstructing geometric shapes from point clouds is a common task that is often accomplished by experts manually modeling geometries in CAD-capable software. State-of-the-art workflows based on fully automatic geometry extraction are limited by point cloud density and memory constraints, and require pre- and post-processing by the user. In this work, we present a framework for interactive, user-driven, feature-assisted geometry reconstruction from arbitrarily sized point clouds. Based on seeded region-growing point cloud segmentation, the user interactively extracts planar pieces of geometry and utilizes contextual suggestions to point out plane surfaces, normal and tangential directions, and edges and corners. We implement a set of feature-assisted tools for high-precision modeling tasks in architecture and urban surveying scenarios, enabling instant-feedback interactive point cloud manipulation on large-scale data collected from real-world building interiors and facades. We evaluate our results through systematic measurement of the reconstruction accuracy, and interviews with domain experts who deploy our framework in a commercial setting and give both structured and subjective feedback. [Display omitted] • Real-world point clouds show strong heterogeneity in size, density, and quality. • Fully automated geometry reconstruction almost always requires human intervention or quality control. • Human-in-the-loop approach avoids cumbersome filter-and-repair post-processing. • Guided technique effectively utilizes human intent to navigate difficult reconstruction scenarios. [ABSTRACT FROM AUTHOR]

Analyzing the evolution of thunderstorms is critical in determining the potential for the development of severe weather events. Existing visualization systems for short‐term weather forecasting (nowcasting) allow for basic analysis and prediction of storm developments. However, they lack advanced visual features for efficient decision‐making. We developed a visual analytics tool for the detection of hazardous thunderstorms and their characterization, using a visual design centered on a reformulated expert task workflow that includes visual features to overview storms and quickly identify high‐impact weather events, a novel storm graph visualization to inspect and analyze the storm structure, as well as a set of interactive views for efficient identification of similar storm cells (known as analogs) in historical data and their use for nowcasting. Our tool was designed with and evaluated by meteorologists and expert forecasters working in short‐term operational weather forecasting of severe weather events. Results show that our solution suits the forecasters' workflow. Our visual design is expressive, easy to use, and effective for prompt analysis and quick decision‐making in the context of short‐range operational weather forecasting. [ABSTRACT FROM AUTHOR]

• An application for cohort exploration of pelvic organ variability in radiotherapy. • Global exploration of anatomical variability in an abstracted tabular view. • Local exploration of anatomical variability with 2D/3D comparative visualizations. • Correlation of anatomical variability with radiation doses and toxicity. • Four application scenarios conducted with domain experts to showcase VAPOR. In radiation therapy (RT) for prostate cancer, changes in patient anatomy during treatment might lead to inadequate tumor coverage and higher irradiation of healthy tissues in the nearby pelvic organs. Exploring and analyzing anatomical variability throughout the course of RT can support the design of more robust treatment strategies, while identifying patients that are prone to radiation-induced toxicity. We present VAPOR , a novel application for the exploration of pelvic organ variability in a cohort of patients, across the entire treatment process. Our application addresses: (i) the global exploration and analysis of anatomical variability in an abstracted tabular view, (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated, and (iii) the correlation of anatomical variability with radiation doses and potential toxicity. The workflow is based on available retrospective cohort data, which include segmentations of the bladder, the prostate, and the rectum through the entire treatment period. VAPOR is applied to four usage scenarios, which were conducted with two medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment adaptation to anatomical changes. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

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 FROM AUTHOR]

Abstract We provide a high-level survey of multiscale molecular visualization techniques, with a focus on application-domain questions, challenges, and tasks. We provide a general introduction to molecular visualization basics and describe a number of domain-specific tasks that drive this work. These tasks, in turn, serve as the general structure of the following survey. First, we discuss methods that support the visual analysis of molecular dynamics simulations. We discuss, in particular, visual abstraction and temporal aggregation. In the second part, we survey multiscale approaches that support the design, analysis, and manipulation of DNA nanostructures and related concepts for abstraction, scale transition, scale-dependent modeling, and navigation of the resulting abstraction spaces. In the third part of the survey, we showcase approaches that support interactive exploration within large structural biology assemblies up to the size of bacterial cells. We describe fundamental rendering techniques as well as approaches for element instantiation, visibility management, visual guidance, camera control, and support of depth perception. We close the survey with a brief listing of important tools that implement many of the discussed approaches and a conclusion that provides some research challenges in the field. Graphical Abstract Unlabelled Image Highlights • Comprehensive overview of new strand of research in visualization, computer graphics, and user interface design. • Survey is organized along generic visualization scenarios: exploration, analysis, presentation supported by specific domain scenarios. • Technological advances made accessible to the readership from the molecular biology domain. [ABSTRACT FROM AUTHOR]

The analysis of multidimensional data has been a topic of continuous research for many years. This type of data can be found in several different areas of science. A common task while analyzing such data is to investigate patterns by interacting with spatializations of the data in a visual domain. Understanding the relation between the underlying dataset characteristics and the technique used to provide its visual representation is of fundamental importance since it can provide a better intuition on what to expect from the spatialization. In this paper, we propose the usage of concepts from non-parametric statistics, namely depth functions, as a quality measure for spatializations. We evaluate the action of multidimensional projection techniques on such estimates. We apply both qualitative and quantitative analyses on four different multidimensional techniques selected according to the properties they aim to preserve. We evaluate them with datasets of different characteristics: synthetic, real world, high dimensional; and contaminated with outliers. As a straightforward application, we propose to use depth information to guide multidimensional projection techniques which rely on interaction through control point selection and positioning. Even for techniques which do not intend to preserve any centrality measure, interesting results can be achieved by separating regions possibly contaminated with outliers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]