Scalable Visualization of Galaxies, Oceans, and Brains

One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Tensor3D: A computer graphics program to simulate 3D real-time deformation and visualization of geometric bodies

Tensor3D is a geometric modeling program with the capacity to simulate and visualize in real-time the deformation, specified through a tensor matrix and applied to triangulated models representing geological bodies. 3D visualization allows the study of deformational processes that are traditionally conducted in 2D, such as simple and pure shears. Besides geometric objects that are immediately available in the program window, the program can read other models from disk, thus being able to import objects created with different open-source or proprietary programs. A strain ellipsoid and a bounding box are simultaneously shown and instantly deformed with the main object. The principal axes of strain are visualized as well to provide graphical information about the orientation of the tensor's normal components. The deformed models can also be saved, retrieved later and deformed again, in order to study different steps of progressive strain, or to make this data available to other programs. The shape of stress ellipsoids and the corresponding Mohr circles defined by any stress tensor can also be represented. The application was written using the Visualization ToolKit, a powerful scientific visualization library in the public domain. This development choice, allied to the use of the Tcl/Tk programming language, which is independent on the host computational platform, makes the program a useful tool for the study of geometric deformations directly in three dimensions in teaching as well as research activities. (C) 2007 Elsevier Ltd. All rights reserved.

Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.

Symbolic fractional dynamics

Fractional dynamics reveals long range memory properties of systems described by means of signals represented by real numbers. Alternatively, dynamical systems and signals can adopt a representation where states are quantified using a set of symbols. Such signals occur both in nature and in man made processes and have the potential of a aftermath as relevant as the classical counterpart. This paper explores the association of Fractional calculus and symbolic dynamics. The results are visualized by means of the multidimensional technique and reveal the association between the fractal dimension and one definition of fractional derivative.

Level Set Methods in Image Processing

This thesis gives an overview of the use of the level set methods in the field of image science. The similar fast marching method is discussed for comparison, also the narrow band and the particle level set methods are introduced. The level set method is a numerical scheme for representing, deforming and recovering structures in an arbitrary dimensions. It approximates and tracks the moving interfaces, dynamic curves and surfaces. The level set method does not define how and why some boundary is advancing the way it is but simply represents and tracks the boundary. The principal idea of the level set method is to represent the N dimensional boundary in the N+l dimensions. This gives the generality to represent even the complex boundaries. The level set methods can be powerful tools to represent dynamic boundaries, but they can require lot of computing power. Specially the basic level set method have considerable computational burden. This burden can be alleviated with more sophisticated versions of the level set algorithm like the narrow band level set method or with the programmable hardware implementation. Also the parallel approach can be used in suitable applications. It is concluded that these methods can be used in a quite broad range of image applications, like computer vision and graphics, scientific visualization and also to solve problems in computational physics. Level set methods and methods derived and inspired by it will be in the front line of image processing also in the future.

A statistical shape model of the human second cervical vertebra.

PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.

Integración de visualización científica molecular en el salón de clases

For some years, Chemistry teachers have used scientific visualization software of molecular models in computing rooms and chemistry laboratories for educational purposes. However, its application in classrooms has been limited. This article describes the integration and use of computer programs for scientific molecular visualization in a traditional classroom. We consider that the improvement of technical aspects of their application and use (usability) has a direct effect on students' understanding of molecular structures (including students' extrinsic motivation), among other factors. Consequently, we developed a guide for the integration of hardware and software of molecular visualization for its use in the classroom.

Concepções de licenciandos em química sobre visualizações no ensino de ciências em dois países: Brasil e Portugal

In this work, the beliefs of undergraduate students from Brazil and Portugal on the use of visual tools in teaching chemistry, which have increasingly been introduced in the areas of teaching/learning in these two countries in recent years, have been investigated. An interpretative analysis of the results shows little familiarity of students with specific points of the theme, beyond a poor conception about the way the visualization tools influence the construction of scientific concepts.

Mittausdatan havainnollistaminen MATLAB animaationa

The visualization of measurement data is important in the fields of engineering for research analysis and presentation purposes. A suitable visualization method for scientific visualization is needed when handling measurement data. Visualization methods and techniques will be presented throughout this work. They are the bases of scientific visualization from the abstract visualization process to the applied techniques suited for each situation. This work also proposes a visualization tool using the MATLAB® software. The tool was designed as general as possible to encompass the most needs in terms of measurement data visualization. It offers possibilities for both static and dynamic visualization of the data.

Fast regridding of large, complex geospatial datasets

In the earth sciences, data are commonly cast on complex grids in order to model irregular domains such as coastlines, or to evenly distribute grid points over the globe. It is common for a scientist to wish to re-cast such data onto a grid that is more amenable to manipulation, visualization, or comparison with other data sources. The complexity of the grids presents a significant technical difficulty to the regridding process. In particular, the regridding of complex grids may suffer from severe performance issues, in the worst case scaling with the product of the sizes of the source and destination grids. We present a mechanism for the fast regridding of such datasets, based upon the construction of a spatial index that allows fast searching of the source grid. We discover that the most efficient spatial index under test (in terms of memory usage and query time) is a simple look-up table. A kd-tree implementation was found to be faster to build and to give similar query performance at the expense of a larger memory footprint. Using our approach, we demonstrate that regridding of complex data may proceed at speeds sufficient to permit regridding on-the-fly in an interactive visualization application, or in a Web Map Service implementation. For large datasets with complex grids the new mechanism is shown to significantly outperform algorithms used in many scientific visualization packages.

Visualização de informação em sistemas científicos

Este trabalho é um estudo sobre a aplicação de técnicas de visualização de informação em sistemas de software científico, i.e., sistemas de software voltados para matemática, ciências e engenharias. Enquanto sistemas dessa natureza normalmente fazem uso da visualização científica e figuram como caso de sucesso nessa área, nem sempre são projetados considerando os princípios de visualização de informação. Esse trabalho tem por objetivo avaliar a aplicação desse conceitos em alguns sistemas reais, desenvolvidos com diferentes níveis de entendimento nessa área de conhecimento e com base nessas experiências propor o desenvolvimento de componentes de software capazes de facilitar a criação de sistemas semelhantes e ao mesmo tempo promover a aplicação destes conceitos.

RR3D: Uma solução para renderização remota de imagens médicas tridimensionais

The visualization of three-dimensional(3D)images is increasigly being sed in the area of medicine, helping physicians diagnose desease. the advances achived in scaners esed for acquisition of these 3d exames, such as computerized tumography(CT) and Magnetic Resonance imaging (MRI), enable the generation of images with higher resolutions, thus, generating files with much larger sizes. Currently, the images of computationally expensive one, and demanding the use of a righ and computer for such task. The direct remote acess of these images thruogh the internet is not efficient also, since all images have to be trasferred to the user´s equipment before the 3D visualization process ca start. with these problems in mind, this work proposes and analyses a solution for the remote redering of 3D medical images, called Remote Rendering (RR3D). In RR3D, the whole hedering process is pefomed a server or a cluster of servers, with high computational power, and only the resulting image is tranferred to the client, still allowing the client to peform operations such as rotations, zoom, etc. the solution was developed using web services written in java and an architecture that uses the scientific visualization packcage paraview, the framework paraviewWeb and the PACS server DCM4CHEE.The solution was tested with two scenarios where the rendering process was performed by a sever with graphics hadwere (GPU) and by a server without GPUs. In the scenarios without GPUs, the soluction was executed in parallel with several number of cores (processing units)dedicated to it. In order to compare our solution to order medical visualization application, a third scenario was esed in the rendering process, was done locally. In all tree scenarios, the solution was tested for different network speeds. The solution solved satisfactorily the problem with the delay in the transfer of the DICOM files, while alowing the use of low and computers as client for visualizing the exams even, tablets and smart phones

Reconstrução e geração de malhas em estruturas biomecânicas tridimensionais para análise por elemento finitos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)