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We present visualizations of recent supercomputer simulations from numerical relativity, exploiting the progress in visualization techniques and numerical methods also from an artistic point of view. The sequences have been compiled into a video tape, showing colliding black holes, orbiting and merging neutron stars as well as collapsing gravitational waves. In this paper we give some background information and provide a glance at the presented sequences.
In this paper we discuss several ways to visualize stationary and non-stationary quantum mechanical systems. We demonstrate an approach for the quantitative interpretation of probability density isovalues which yields a reasonable correlation between isosurfaces for different timesteps. As an intuitive quantity for visualizing the momentum of a quantum system we propose the probability flow density which can be treated by vector field visualization techniques. Finally, we discuss the visualization of non-stationary systems by a sequence of single timestep images.
\noindent The size of data sets produced on remote supercomputer facilities frequently exceeds the processing capabilities of local visualization workstations. This phenomenon increasingly limits scientists when analyzing results of large-scale scientific simulations. That problem gets even more prominent in scientific collaborations, spanning large virtual organizations, working on common shared sets of data distributed in Grid environments. In the visualization community, this problem is addressed by distributing the visualization pipeline. In particular, early stages of the pipeline are executed on resources closer to the initial (remote) locations of the data sets. \noindent This paper presents an efficient technique for placing the first two stages of the visualization pipeline (data access and data filter) onto remote resources. This is realized by exploiting the ``extended retrieve'' feature of GridFTP for flexible, high performance access to very large HDF5 files. We reduce the number of network transactions for filtering operations by utilizing a server side data processing plugin, and hence reduce latency overhead compared to GridFTP partial file access. The paper further describes the application of hierarchical rendering techniques on remote uniform data sets, which make use of the remote data filtering stage.
Analysis of phenomena that simultaneously occur on quite different spatial and temporal scales require adaptive, hierarchical schemes to reduce computational and storage demands. For data represented as grid functions, the key are adaptive, hierarchical, time-dependent grids that resolve spatio-temporal details without too much redundancy. Here, so-called AMR grids gain increasing popularity. For visualization and feature identification/tracking, the underlying continuous function has to be faithfully reconstructed by spatial and temporal interpolation. Well designed interpolation methods yield better results and help to reduce the amount of data to be stored. We address the problem of temporal interpolation of AMR grid data, e.g.\ for creation of smooth animations or feature tracking. Intermediate grid hierarchies are generated by merging the cells on all refinement levels that are present in the key frames considered. Utilizing a clustering algorithm a structure of nested grids is induced on the resulting collection of cells. The grid functions are mapped to the intermediate hierarchy, thus allowing application of appropriate interpolation techniques.
Tensor Splats
(2003)
An improved general-purpose technique for the visualization of symmetric positive definite tensor fields of rank two is described. It is based on a splatting technique that is built from tiny transparent glyph primitives which are capable to incorporate the full directional information content of a tensor. The result is an information-rich image that allows to read off the preferred directions in a tensor field at each point of a three-dimensional volume or two-dimensional surface. It is useful for analyzing slices or volumes of a three-dimensional tensor field and can be overlayed with standard volume rendering or color mapping. The application of the rendering technique is demonstrated on general relativistic data and the diffusion tensor field of a human brain.
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.
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.
Die Autoren schreiben dieses Papier aus der eingeschränkten Sicht der Mathematik und der Informationstechnik. Um den speziellen Beitrag dieser Disziplinen überhaupt diskutieren zu können, sehen wir uns jedoch gezwungen, einen Rahmen abzustecken, den wir für das Jahr 2020 vorhersehen -- nach Wahrscheinlichkeit und aus unserem engeren fachlichen Blickwinkel. Vorab bitten wir schon einmal bei den medizinischen Fachleuten um Nachsicht, wenn wir uns in ihrem Revier allzu dillettantisch bewegen. Vielleicht fördert aber auch unser eingeschränkter Blickwinkel ansonsten unbedachte Aspekte zutage -- das hoffen wir zumindest.
Purpose/Aims of the Study: Bone’s hierarchical structure can be visualized using a variety of methods. Many techniques, such as light and electron microscopy generate two-dimensional (2D) images, while micro computed tomography (μCT) allows a direct representation of the three-dimensional (3D) structure. In addition, different methods provide complementary structural information, such as the arrangement of organic or inorganic compounds. The overall aim of the present study is to answer bone research questions by linking information of different 2D and 3D imaging techniques. A great challenge in combining different methods arises from the fact that they usually reflect different characteristics of the real structure.
Materials and Methods: We investigated bone during healing by means of μCT and a couple of 2D methods. Backscattered electron images were used to qualitatively evaluate the tissue’s calcium content and served as a position map for other experimental data. Nanoindentation and X-ray scattering experiments were performed to visualize mechanical and structural properties. Results: We present an approach for the registration of 2D data in a 3D μCT reference frame, where scanning electron microscopies serve as a methodic link. Backscattered electron images are perfectly suited for registration into μCT reference frames, since both show structures based on the same physical principles. We introduce specific registration tools that have been developed to perform the registration process in a semi-automatic way.
Conclusions: By applying this routine, we were able to exactly locate structural information (e.g. mineral particle properties) in the 3D bone volume. In bone healing studies this will help to better understand basic formation, remodeling and mineralization processes.
One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned task by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons.
Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits.
The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa.