734 research outputs found
Model-Based Visualization for Intervention Planning
No full textComputer support for intervention planning is often a two-stage process: In a first stage, the relevant segmentation target structures are identified and delineated. In a second stage, image analysis results are employed for the actual planning process. In the first stage, model-based segmentation techniques are often used to reduce the interaction effort and increase the reproducibility. There is a similar argument to employ model-based techniques for the visualization as well. With increasingly more visualization options, users have many parameters to adjust in order to generate expressive visualizations. Surface models may be smoothed with a variety of techniques and parameters. Surface visualization and illustrative rendering techniques are controlled by a large set of additional parameters. Although interactive 3d visualizations should be flexible and support individual planning tasks, appropriate selection of visualization techniques and presets for their parameters is needed. In this chapter, we discuss this kind of visualization support. We refer to model-based visualization to denote the selection and parameterization of visualization techniques based on 'a priori knowledge concerning visual perception, shapes of anatomical objects and intervention planning tasks
HCI in Medical Visualization
No full textResearch in medical visualization lead to a remarkable collection
of algorithms for efficiently exploring medical imaging data, such
as CT, MRI and DTI. However, widespread use of such algorithms requires careful parameterization, integration of individual algorithms in solutions for real-world problems in diagnosis, treatment planning and intraoperative navigation. In the field of HCI, input devices, interaction techniques as well as a process for achieving usable, useful, and attractive user interfaces are explored. Findings from HCI may serve as a starting point to significantly improve visual computing solutions in medical diagnosis and treatment. We discuss general issues, such as input devices for medical visualization, and selected examples
Describing Abstraction in Rendered Images through Figure Captions
No full textion in Rendered Images through Figure Captions Knut Hartmann, 1 Bernhard Preim, 2 Thomas Strothotte 2 1 Institute for Knowledge and Language Engineering 2 Department of Simulation and Graphics Faculty of Computer Science Otto-von-Guericke University of Magdeburg Universitatsplatz 2 D-39106 Magdeburg, Germany [email protected] [email protected] Abstract We analyze illustration and abstraction techniques used in rendered images. We argue that it is important to convey these techniques to viewers of such images to enhance the process of image understanding. This leads us to derive methods for automatically generating figure captions for rendered images which describe the abstraction carried out. We apply this concept to computer generated anatomic illustrations. Strategies for the content selection for figure captions, for setting user preferences and for updating figure captions are described. Several approaches to the realization of figure..
Staircase-Aware Smoothing of Medical Surface Meshes
No full textThe evaluation of spatial relationships between anatomic structures is a major task in surgical planning. Surface models generated from medical image data (intensity, binary) are often used for visualization and 3D measurement of extents and distances between neighboring structures. In applications for intervention or radiation treatment planning, the surface models should exhibit a natural look (referring to smoothness of the surface), but also be accurate. Smoothing algorithms allow to reduce artifacts from mesh generation, but often degrade accuracy. In particular, relevant features may be removed and distances between adjacent structures get changed. Thus, we present a modification to common mesh smoothing algorithms, which allows to focus the smoothing effect directly to previously identified staircase artifacts. This allows to preserve non-artifact features. The approach has been applied to various data to demonstrate the suitability for different anatomical shapes. The results are compared to the ones of standard uniform mesh smoothing algorithms and are evaluated regarding smoothness and accuracy with respect to the application within surgical planning.Eurographics Workshop on Visual Computing for Biology and Medicin
Importance-Driven Structure Categorization for 3D Surgery Planning
No full textWe present an importance-driven categorization approach to automatically gather all currently required structures for the surgery planning process. Therefore, we analyzed common demands for tumor intervention planning and integrated domain knowledge to enable a determination of the relevant structures for various surgical questions. The categorization of structures in focus, focus-relevant and context is defined and initiated by the question. Our method uses the structure's specific meta data and geometric information to determine an importance value for each structure automatically. This importance value encodes the structure's priority for the current question and defines the structure's category. Furthermore, this value can be used to define a structure-specific visual style to generate expressive 3D surgery planning visualizations.Eurographics Workshop on Visual Computing for Biology and Medicin
Streamlines for Illustrative Real-Time Rendering
No full textLine drawing techniques are important methods to illustrate shapes. Existing feature line methods, e.g., suggestive contours, apparent ridges, or photic extremum lines, solely determine salient regions and illustrate them with separate lines. Hatching methods convey the shape by drawing a wealth of lines on the whole surface. Both approaches are often not sufficient for a faithful visualization of organic surface models, e.g., in biology or medicine. In this paper, we present a novel object-space line drawing algorithm that conveys the shape of such surface models in real-time. Our approach employs contour- and feature-based illustrative streamlines to convey surface shape (ConFIS). For every triangle, precise streamlines are calculated on the surface with a given curvature vector field. Salient regions are detected by determining maxima and minima of a scalar field. Compared with existing feature lines and hatching methods, ConFIS uses the advantages of both categories in an effective and flexible manner. We demonstrate this with different anatomical and artificial surface models. In addition, we conducted a qualitative evaluation of our technique to compare our results with exemplary feature line and hatching methods.Computer Graphics Foru
Adapted Surface Visualization of Cerebral Aneurysms with Embedded Blood Flow Information
No full textCerebral aneurysms are a vascular dilatation induced by a pathological change of the vessel wall and often require treatment to avoid rupture. Therefore, it is of main interest, to estimate the risk of rupture, to gain a deeper understanding of aneurysm genesis, and to plan an actual intervention, the surface morphology and the internal blood flow characteristics. Visual exploration is primarily used to understand such complex and variable type of data. Since the blood flow data is strongly influenced by the surrounding vessel morphology both have to be visually combined to efficiently support visual exploration. Since the flow is spatially embedded in the surrounding aneurysm surface, occlusion problems have to be tackled. Thereby, a meaningful visual reduction of the aneurysm surface that still provides morphological hints is necessary. We accomplish this by applying an adapted illustrative rendering style to the aneurysm surface. Our contribution lies in the combination and adaption of several rendering styles, which allow us to reduce the problem of occlusion and avoid most of the disadvantages of the traditional semi-transparent surface rendering, like ambiguities in perception of spatial relationships. In interviews with domain experts, we derived visual requirements. Later, we conducted an initial survey with 40 participants (13 medical experts of them), which leads to further improvements of our approach.Eurographics Workshop on Visual Computing for Biology and Medicin
Visual computing for medicine : theory, algorithms, and applications, 2nd ed./ Preim
No full textxxiii, p.812.: ill.; 24 c
Visual computing for medicine : theory, algorithms, and applications, 2nd ed./ Preim
No full textxxiii, p.812.: ill.; 24 c
Illustrative Focus+Context Approaches in Interactive Volume Visualization
No full textIllustrative techniques are a new and exciting direction in visualization research. Traditional techniques which have been used by scientific illustrators for centuries are re-examined under the light of modern computer technology. In this paper, we discuss the use of the focus+context concept for the illustrative visualization of volumetric data. We give an overview of the state-of-the-art and discuss recent approaches which employ this concept in novel ways
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