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Visualizations of vascular structures are frequently used in radiological investigations to detect and analyze vascular diseases. Obstructions of the blood flow through a vessel are one of the main interests of physicians, and several methods have been proposed to aid the visual assessment of calcifications on vessel walls. Curved Planar Reformation (CPR) is a wide-spread method that is designed for peripheral arteries which exhibit one dominant direction. To analyze the lumen of arbitrarily oriented vessels, Centerline Reformation (CR) has been proposed. Both methods project the vascular structures into 2D image space in order to reconstruct the vessel lumen. In this paper, we propose Curved Surface Reformation (CSR), a technique that computes the vessel lumen fully in 3D. This offers high-quality interactive visualizations of vessel lumina and does not suffer from problems of earlier methods such as ambiguous visibility cues or premature discretization of centerline data. Our method maintains exact visibility information until the final query of the 3D lumina data. We also present feedback from several domain experts.

This paper describes an advanced visualization method for the analysis of defects in industrial 3D X-Ray Computed Tomography (XCT) data. We present a novel way to explore a high number of individual objects in a dataset, e.g., pores, inclusions, particles, fibers, and cracks demonstrated on the special application area of pore extraction in carbon fiber reinforced polymers (CFRP). After calculating the individual object properties volume, dimensions and shape factors, all objects are clustered into a mean object (MObject). The resulting MObject parameter space can be explored interactively. To do so, we introduce the visualization of mean object sets (MObject Sets) in a radial and a parallel arrangement. Each MObject may be split up into sub-classes by selecting a specific property, e.g., volume or shape factor, and the desired number of classes. Applying this interactive selection iteratively leads to the intended classifications and visualizations of MObjects along the selected analysis path. Hereby the given different scaling factors of the MObjects down the analysis path are visualized through a visual linking approach. Furthermore the representative MObjects are exported as volumetric datasets to serve as input for successive calculations and simulations. In the field of porosity determination in CFRP non-destructive testing practitioners use representative MObjects to improve ultrasonic calibration curves. Representative pores also serve as input for heat conduction simulations in active thermography. For a fast overview of the pore properties in a dataset we propose a local MObjects visualization in combination with a color-coded homogeneity visualization of cells. The advantages of our novel approach are demonstrated using real world CFRP specimens. The results were evaluated through a questionnaire in order to determine the practicality of the MObjects visualization as a supportive tool for domain specialists.

Scientists, engineers, and analysts are confronted with ever larger and more complex sets of data, whose analysis poses special challenges. In many situations it is necessary to compare two or more datasets. Hence there is a need for comparative visualization tools to help analyze differences or similarities among datasets. In this paper an approach for comparative visualization for sets of images is presented. Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost. This paper introduces a new method for visualizing differences and similarities in large sets of images which preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application which allows users to rapidly explore the space of differences and drill-down on particular features. We demonstrate the flexibility of our approach by applying it to multiple distinct domains.

Many application domains deal with multi-variate data that consist of both categorical and numerical information. Smallmultiple displays are a powerful concept for comparing such data by juxtaposition. For comparison by overlay or by explicit encoding of computed differences, however, a specification of references is necessary. In this paper, we present a formal model for defining semantically meaningful comparisons between many categories in a small-multiple display. Based on pivotized data that are hierarchically partitioned by the categories assigned to the x and y axis of the display, we propose two alternatives for structure-based comparison within this hierarchy. With an absolute reference specification, categories are compared to a fixed reference category. With a relative reference specification, in contrast, a semantic ordering of the categories is considered when comparing them either to the previous or subsequent category each. Both reference specifications can be defined at multiple levels of the hierarchy (including aggregated summaries), enabling a multitude of useful comparisons. We demonstrate the general applicability of our model in several application examples using different visualizations that compare data by overlay or explicit encoding of differences.

The combination of volume data acquired by multiple modalities has been recognized as an important but challenging task. Modalities often differ in the structures they can delineate and their joint information can be used to extend the classification space. However, they frequently exhibit differing types of artifacts which makes the process of exploiting the additional information non-trivial. In this paper, we present a framework based on an information-theoretic measure of isosurface similarity between different modalities to overcome these problems. The resulting similarity space provides a concise overview of the differences between the two modalities, and also serves as the basis for an improved selection of features. Multimodal classification is expressed in terms of similarities and dissimilarities between the isosurfaces of individual modalities, instead of data value combinations. We demonstrate that our approach can be used to robustly extract features in applications such as dual energy computed tomography of parts in industrial manufacturing., (© 2011 IEEE)

Better understanding of hemodynamics conceivably leads to improved diagnosis and prognosis of cardiovascular diseases. Therefore, an elaborate analysis of the blood-flow in heart and thoracic arteries is essential. Contemporary MRI techniques enable acquisition of quantitative time-resolved flow information, resulting in 4D velocity fields that capture the blood-flow behavior. Visual exploration of these fields provides comprehensive insight into the unsteady blood-flow behavior, and precedes a quantitative analysis of additional blood-flow parameters. The complete inspection requires accurate segmentation of anatomical structures, encompassing a time-consuming and hard-to-automate process, especially for malformed morphologies. We present a way to avoid the laborious segmentation process in case of qualitative inspection, by introducing an interactive virtual probe. This probe is positioned semi-automatically within the blood-flow field, and serves as a navigational object for visual exploration. The difficult task of determining position and orientation along the view-direction is automated by a fitting approach, aligning the probe with the orientations of the velocity field. The aligned probe provides an interactive seeding basis for various flow visualization approaches. We demonstrate illustration-inspired particles, integral lines and integral surfaces, conveying distinct characteristics of the unsteady blood-flow. Lastly, we present the results of an evaluation with domain experts, valuing the practical use of our probe and flow visualization techniques., (© 2011 IEEE)

Insight into the dynamics of blood-flow considerably improves the understanding of the complex cardiovascular system and its pathologies. Advances in MRI technology enable acquisition of 4D blood-flow data, providing quantitative blood-flow velocities over time. The currently typical slice-by-slice analysis requires a full mental reconstruction of the unsteady blood-flow field, which is a tedious and highly challenging task, even for skilled physicians. We endeavor to alleviate this task by means of comprehensive visualization and interaction techniques. In this paper we present a framework for pre-clinical cardiovascular research, providing tools to both interactively explore the 4D blood-flow data and depict the essential blood-flow characteristics. The framework encompasses a variety of visualization styles, comprising illustrative techniques as well as improved methods from the established field of flow visualization. Each of the incorporated styles, including exploded planar reformats, flow-direction highlights, and arrow-trails, locally captures the blood-flow dynamics and may be initiated by an interactively probed vessel cross-section. Additionally, we present the results of an evaluation with domain experts, measuring the value of each of the visualization styles and related rendering parameters.

Neurobiology investigates how anatomical and physiological relationships in the nervous system mediate behavior. Molecular genetic techniques, applied to species such as the common fruit fly Drosophila melanogaster, have proven to be an important tool in this research. Large databases of transgenic specimens are being built and need to be analyzed to establish models of neural information processing. In this paper we present an approach for the exploration and analysis of neural circuits based on such a database. We have designed and implemented BrainGazer, a system which integrates visualization techniques for volume data acquired through confocal microscopy as well as annotated anatomical structures with an intuitive approach for accessing the available information. We focus on the ability to visually query the data based on semantic as well as spatial relationships. Additionally, we present visualization techniques for the concurrent depiction of neurobiological volume data and geometric objects which aim to reduce visual clutter. The described system is the result of an ongoing interdisciplinary collaboration between neurobiologists and visualization researchers.

Visually assessing the effect of the coronary artery anatomy on the perfusion of the heart muscle in patients with coronary artery disease remains a challenging task. We explore the feasibility of visualizing this effect on perfusion using a numerical approach. We perform a computational simulation of the way blood is perfused throughout the myocardium purely based on information from a three-dimensional anatomical tomographic scan. The results are subsequently visualized using both three-dimensional visualizations and bull's eye plots, partially inspired by approaches currently common in medical practice. Our approach results in a comprehensive visualization of the coronary anatomy that compares well to visualizations commonly used for other scanning technologies. We demonstrate techniques giving detailed insight in blood supply, coronary territories and feeding coronary arteries of a selected region. We demonstrate the advantages of our approach through visualizations that show information which commonly cannot be directly observed in scanning data, such as a separate visualization of the supply from each coronary artery. We thus show that the results of a computational simulation can be effectively visualized and facilitate visually correlating these results to for example perfusion data.

Event-based systems monitor business processes in real time. The event-tunnel visualization sees the stream of events captured from such systems as a cylindrical tunnel. The tunnel allows for back-tracing business incidents and exploring event patterns' root causes. The authors couple this visualization with tools that let users search for relevant events within a data repository.

In volume rendering, it is very difficult to simultaneously visualize interior and exterior structures while preserving clear shape cues. Highly transparent transfer functions produce cluttered images with many overlapping structures, while clipping techniques completely remove possibly important context information. In this paper, we present a new model for volume rendering, inspired by from illustration. It provides a means of interactively inspecting the interior of a volumetric data set in a feature-driven way which retains context information. The context-preserving volume rendering model uses a function of shading intensity, gradient magnitude, distance to the eye point, and previously accumulated opacity to selectively reduce the opacity in less important data regions. It is controlled by two user-specified parameters. This new method represents an alternative to conventional clipping techniques, sharing their easy and intuitive user control, but does not suffer from the drawback of missing context information.

Caricatures are pieces of art depicting persons or sociological conditions in a non-veridical way. In both cases caricatures are referring to a reference model. The deviations from the reference model are the characteristic features of the depicted subject. Good caricatures exaggerate the characteristics of a subject in order to accent them. The concept of caricaturistic visualization is based on the caricature metaphor. The aim of caricaturistic visualization is an illustrative depiction of characteristics of a given dataset by exaggerating deviations from the reference model. We present the general concept of caricaturistic visualization as well as a variety of examples. We investigate different visual representations for the depiction of caricatures. Further, we present the caricature matrix, a technique to make differences between datasets easily identifiable.

This paper presents importance-driven feature enhancement as a technique for the automatic generation of cut-away and ghosted views out of volumetric data. The presented focus+context approach removes or suppresses less important parts of a scene to reveal more important underlying information. However, less important parts are fully visible in those regions, where important visual information is not lost, i.e., more relevant features are not occluded. Features within the volumetric data are first classified according to a new dimension, denoted as object importance. This property determines which structures should be readily discernible and which structures are less important. Next, for each feature, various representations (levels of sparseness) from a dense to a sparse depiction are defined. Levels of sparseness define a spectrum of optical properties or rendering styles. The resulting image is generated by ray-casting and combining the intersected features proportional to their importance (importance compositing). The paper includes an extended discussion on several possible schemes for levels of sparseness specification. Furthermore, different approaches to importance compositing are treated.

This paper proposes comparison and visualization techniques to carry out parameter studies for the special application area of dimensional measurement using 3D X-ray computed tomography (3DCT). A dataset series is generated by scanning a specimen multiple times by varying parameters of an industrial 3DCT device. A high-resolution series is explored using our planar-reformatting-based visualization system. We present a novel multi-image view and an edge explorer for comparing and visualizing gray values and edges of several datasets simultaneously. Visualization results and quantitative data are displayed side by side. Our technique is scalable and generic. It can be effective in various application areas like parameter studies of imaging modalities and dataset artifact detection. For fast data retrieval and convenient usability, we use bricking of the datasets and efficient data structures. We evaluate the applicability of the proposed techniques in collaboration with our company partners. [ABSTRACT FROM AUTHOR]

In traditional illustration the choice of appropriate styles and rendering techniques is guided by the intention of the artist. For illustrative volume visualizations it is difficult to specify the mapping between the 3D data and the visual representation that preserves the intention of the user. The semantic layers concept establishes this mapping with a linguistic formulation of rules that directly map data features to rendering styles. With semantic layers fuzzy logic is used to evaluate the user defined illustration rules in a preprocessing step. In this paper we introduce interaction-dependent rules that are evaluated for each frame and are therefore computationally more expensive. Enabling interaction-dependent rules, however, allows the use of a new class of semantics, resulting in more expressive interactive illustrations. We show that the evaluation of the fuzzy logic can be done on the graphics hardware enabling the efficient use of interaction-dependent semantics. Further we introduce the flat rendering mode and discuss how different rendering parameters are influenced by the rule base. Our approach provides high quality illustrative volume renderings at interactive frame rates, guided by the specification of illustration rules. [ABSTRACT FROM AUTHOR]

Exploded views are an illustration technique where an object is partitioned into several segments. These segments are displaced to reveal otherwise hidden detail. In this paper we apply the concept of exploded views to volumetric data in order to solve the general problem of occlusion. In many cases an object of interest is occluded by other structures. While transparency or cutaways can be used to reveal a focus object, these techniques remove parts of the context information. Exploded views, on the other hand, do not suffer from this drawback. Our approach employs a force-based model: the volume is divided into a part configuration controlled by a number of forces and constraints. The focus object exerts an explosion force causing the parts to arrange according to the given constraints. We show that this novel and flexible approach allows for a wide variety of explosion-based visualizations including view-dependent explosions. Furthermore, we present a high-quality GPU-based volume ray casting algorithm for exploded views which allows rendering and interaction at several frames per second. [ABSTRACT FROM AUTHOR]

The article profiles Eduard Gröller, a professor at the Vienna University of Technology's Institute of Computer Graphics and Algorithms (ICGA). Gröller received his doctorate degree from Vienna University. His research focuses on computer graphics, flow visualization and information visualization. He co-authored over 180 scientific publications and also served on various programs and paper committees.

Abstract: In this paper, we introduce a novel framework for the compositing of interactively rendered 3D layers tailored to the needs of scientific illustration. Currently, traditional scientific illustrations are produced in a series of composition stages, combining different pictorial elements using 2D digital layering. Our approach extends the layer metaphor into 3D without giving up the advantages of 2D methods. The new compositing approach allows for effects such as selective transparency, occlusion overrides, and soft depth buffering. Furthermore, we show how common manipulation techniques such as masking can be integrated into this concept. These tools behave just like in 2D, but their influence extends beyond a single viewpoint. Since the presented approach makes no assumptions about the underlying rendering algorithms, layers can be generated based on polygonal geometry, volumetric data, point-based representations, or others. Our implementation exploits current graphics hardware and permits real-time interaction and rendering. [ABSTRACT FROM AUTHOR]