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We describe a novel method for continuously transforming two triangulated models of arbitrary topology into each other. Equal global topology for both objects is assumed, extensions for genus changes during metamorphosis are provided. The proposed method addresses the major challenge in 3D metamorphosis, namely specifying the morphing process intuitively, with minimal user interaction and sufficient detail. Corresponding regions and point features are interactively identified. These regions are parametrized automatically and consistently, providing a basis for smooth interpolation. Utilizing suitable 3D interaction techniques a simple and intuitive control over the whole morphing process is offered.
By combining techniques of preparation, histology, confocal microscopy, data visualization and data processing, we have created and recently published a standard brain model for drosophila and honey bee brains. This report describes the algorithms and implementation of the corresponding software modules. At the same time it serves as a user's guide for scientist who want to reproduce the results for differerent species or mutants.
Segmentation tools in medical imaging are either based on editing geometric curves or on the assignment of region labels to image voxels. While the first approach is well suited to describe smooth contours at subvoxel accuracy, the second approach is conceptually more simple and guarantees a unique classification of image areas. However, contours extracted from labeled images typically exhibit strong staircase artifacts and are not well suited to represent smooth tissue boundaries. In this paper we describe how this drawback can be circumvented by supplementing region labels with additional weights. We integrated our approach into an interactive segmentation system providing a well-defined set of manual and semi-automatic editing tools. All tools update both region labels as well as the corresponding weights simultaneously, thus allowing one to define segmentation results at high resolution. We applied our techniques to generate 3D polygonal models of anatomical structures.
A new technique for interactive vector field visualization using large numbers of properly illuminated field lines is presented. Taking into account ambient, diffuse, and specular reflection terms as well as transparency and depth cueing, we employ a realistic shading model which significantly increases quality and realism of the resulting images. While many graphics workstations offer hardware support for illuminating surface primitives, usually no means for an accurate shading of line primitives are provided. However, we show that proper illumination of lines can be implemented by exploiting the texture mapping capabilities of modern graphics hardware. In this way high rendering performance with interactive frame rates can be achieved. We apply the technique to render large numbers of integral curves of a vector field. The impression of the resulting images can be further improved by a number of visual enhancements, like transparency and depth-cueing. We also describe methods for controlling the distribution of field lines in space. These methods enable us to use illuminated field lines for interactive exploration of vector fields.
\small Many interesting phenomena in molecular systems like interactions between macro-molecules, protein-substrate docking, or channeling processes in membranes are gouverned to a high degree by classical Coulomb or van-der-Waals forces. The visualization of these force fields is important for verifying numerical simulations. Moreover, by inspecting the forces visually we can gain deeper insight into the molecular processes. Up to now the visualization of vector fields is quite unusual in computational chemistry. In fact many commercial software packages do not support this topic at all. The reason is not that vector fields are considered unimportant, but mainly because of the lack of adequate visualization methods. In this paper we survey a number of methods for vector field visualization, ranging from well-known concepts like arrow or streamline plots to more advanced techniques like line integral convolution, and show how these can be applied to computational chemistry. A combination of the most meaningful methods in an interactive 3D visualization environment can provide a powerful tool box for analysing simulations in molecular dynamics.
HyperPlan is a software system for performing 3D-simulations and treatment planning in regional hyperthermia. It allows the user to understand the complex effects of electromagnetic wave propagation and heat transport inside a patient's body. Optimized power amplitudes and phase settings can be calculated for the BSD radiowave applicators Sigma 60 and Sigma 2000 (eye-applicator). HyperPlan is built on top of the modular, object-oriented visualization system Amira. This system already contains powerful algorithms for image processing, geometric modelling and 3D graphics display. HyperPlan provides a number of hyperthermia-specific modules, allowing the user to create 3D tetrahedral patient models suitable for treatment planning. In addition, all numerical simulation modules required for hyperthermia simulation are part of HyperPlan. This guide provides a step-by-step introduction to hyperthermia planning using HyperPlan. It also describes the usage of the underlying visualization system Amira.
Polygonale Schädelmodelle bilden ein wichtiges Hilfsmittel für computergestützte Planungen im Bereich der plastischen Chirurgie. Wir beschreiben, wie derartige Modelle automatisch aus hochaufgelösten CT-Datensätzen erzeugt werden können. Durch einen lokal steuerbaren Simplifizierungsalgorithmus werden die Modelle so weit vereinfacht, daß auch auf kleineren Graphikcomputern interaktives Arbeiten möglich wird. Die Verwendung eines speziellen Transparenzmodells ermöglicht den ungehinderten Blick auf die bei der Planung relevanten Knochenstrukturen und läßt den Benutzer zugleich die Kopfumrisse des Patienten erkennen.
Line Integral Convolution (LIC) is a powerful technique for generating striking images and animations from vector data. Introduced in 1993, the method has rapidly found many application areas, ranging from computer arts to scientific visualization. Based upon locally filtering an input texture along a curved stream line segment in a vector field, it is able to depict directional information at high spatial resolutions. We present a new method for computing LIC images, which minimizes the total number of stream lines to be computed and thereby reduces computational costs by an order of magnitude compared to the original algorithm. Our methods utilizes fast, error-controlled numerical integrators. Decoupling the characteristic lengths in vector field grid, input texture and output image, it allows to compute filtered images at arbitrary resolution. This feature is of great significance in computer animation as well as in scientific visualization, where it can be used to explore vector data by smoothly enlarging structure of details. We also present methods for improved texture animation, employing constant filter kernels only. To obtain an optimal motion effect, spatial decay of correlation between intensities of distant pixels in the output image has to be controlled. This is achieved by blending different phase shifted box filter animations and by adaptively rescaling the contrast of the output frames.
In this thesis we develop new methods for visualizing vector fields which specifically address three design goals: accuracy, performance, and cognition. Our methods will be general-purpose and can be applied to arbitrary vector fields in two- and three-dimensional space. The methodology behind our approach is {\em texture-based visualization}. Texture-based visualization methods imitate techniques known from experimental flow visualization, namely, the observation of randomly dispersed particles or dye injection patterns. Instead of depicting individual lines or symbols, a contiguous high-resolution image or texture is generated. This texture clearly reveals the directional structure of the field. In this way intuitive insight can be obtained and even small details of the field become visible. However, it remains unclear what kind of textures are best suited for our purpose. How do we generate them? Can we apply these methods in three-dimensional space? In particular, we focus on a technique known as {\em line integral convolution} or LIC. This method turns out to be quite versatile and well-suited for visualizing many interesting vector fields. LIC images display the integral curves or field lines of a vector field at high spatial resolution. Although conceptually quite simple, line integral convolution implies a number of interesting mathematical and algorithmic questions.
Line integral convolution (LIC) has become a well-known and popular method for visualizing vector fields. The method works by convolving a random input texture along the integral curves of the vector field. In order to accelerate image synthesis significantly, an efficient algorithm has been proposed that utilizes pixel coherence in field line direction. This algorithm, called ``fast LIC'', originally was restricted to simple box-type filter kernels. Here we describe a generalization of fast LIC for piecewise polynomial filter kernels. Expanding the filter kernels in terms of truncated power functions allows us to exploit a certain convolution theorem. The convolution integral is expressed as a linear combination of repeated integrals (or repeated sums in the discrete case). Compared to the original algorithm the additional expense for using higher order filter kernels, e.g.\ of B-spline type, is very low. Such filter kernels produce smoother, less noisier results than a box filter. This is evident from visual investigation, as well as from analysis of pixel correlations. Thus, our method represents a useful extension of the fast LIC algorithm for the creation of high-quality LIC images.