基于VTK的医学图像可视化三维重建

医学三维数据场可视化是当前科学计算可视化应用的重点,具有重要的学术意义和应用价值.体绘制是该技术的一个主要的方法.在VTK(Visualization Toolkit)类库提供可视化与显示功能的基础上,主要讨论了光线投射算法进行体数据的绘制的特点,同时采用了包围盒技术改善了光线投射算法的绘制速度.实验结果表明,图像的质量在没有受到影响的前提下,图像的绘制速度得到了大幅度的提高,同时证明了VTK是医学三维数据场可视化的有力工具.     

基于VTK技术的可视化研究

可视化工具（Visualization ToolKit）是一个面向对象的可视化类库，它为从事可视化工具开发的广大科研工作者提供直接的技术支持。本文介绍了使用VTK环境的建立，工作机制以及构成VTK对象模型的组成部分。最后给出了一个可视化的实现。     

基于VTK的海战场电磁信息可视化技术研究

文章从信息可视化的角度,对海战场电磁环境的信息特征进行了初步分析,从不同的角度阐述了可用于电磁数据表征的多种信息呈现方式和方法,说明了基于VTK的海战场电磁信息可视化呈现的基本方法和步骤,并结合VTK工具包,对海战场局部电磁信息进行了数据描述和体视化呈现。     

基于VTK的考古建模系统

采用VC＋＋6．0作为开发平台，引入三维可视化类库VTK，实现了金沙遗址高密度探测考古数据的建模。建模前采用模糊聚类分析方法实现了考古数据的分割，最终将考古模型显示给用户，并实现与用户的交互。     

基于VTK的三维纹理映射方法的实现及其应用

VTK是最著名的可视化软件开发包之一,三维纹理映射也是可视化领域的关键技术,但目前VTK不支持三维纹理。通过分析VTK的工作机制,对VTK进行扩充使之支持三维纹理映射;然后应用三维纹理映射方法实现了在三维几何模型叠加三维数据场,并将该方法应用于自主研发的可视化系统SVIP（Scientific Visualization Integrated Platform）,并取得了良好的效果。     

空间电磁场三维可视化技术研究

为研究战场中典型电磁环境及其对低空巡航导弹的影响,将虚拟现实技术和三维场数据可视化方法结合在一起,通过在战场场景中重构三维等值曲面,把战场中典型电磁场计算模型得到的大量点数据转变成形象直观的,实时交互的三维图像信息,全面表现了战场的地理环境、电磁场的分布等情况,为战场决策和控制提供了依据和帮助.     

复杂电磁环境建模与可视化研究综述

复杂电磁环境建模与可视化研究在民用通信、军用电子战领域的应用不断发展。在介绍了复杂电磁环境基本概念的基础上,首先系统阐述了复杂电磁环境建模的理论方法和数据场的可视化具体方法。然后对国内外复杂电磁环境建模与可视化研究现状进行了分析,对复杂电磁环境中雷达这一主要设备的电磁环境建模进行了研究,并对模型的复杂度、预测精度进行了总结与比较;针对电磁体数据场数据量的海量特性,对电磁体数据场可视化的基本思想、加速技术、适用范围分别从图形硬件加速和软件算法优化两方面进行了归纳与总结;阐述了仿真系统的总体框架设计思想,并设计了一个复杂电磁环境仿真可视化系统。最后对复杂电磁环境建模与可视化未来研究方向进行了展望。     

基于VTK的图像三维可视化系统

图像的三维可视化可以通过可视化工具包（VTK）提供的API实现。VTK是图像可视化的开法工具包,它把可视化的算法封装起来,利用简单的代码生成所需图形。基于VTK的图像三维可视化系统阐述了如何借助VTKAPI读入二维图像序列、操作二维图像、重建三维图像以及进行三维图像可视化的全套方案,为可视化观察二维图像提供了有益的途径。     

基于VTK的医学三维可视化分析系统

计算机断层扫描、核磁共振等生成的二维DICOM数据已被广泛应用在现代临床医疗诊断中,但其直观性差,使诊断的效率低下,并且对医生的经验要求高.对此,针对医学体数据场,以可视化类库VTK为基础,在Windows平台上以Visual C 为开发工具,研究实现了一个医学三维可视化分析系统.主要讨论了采用外接球面法改善光线投射算法绘制速度的改进的体数据绘制方法,以及任意方向虚拟切片的提取和虚拟切片内插值问题.系统可以对重建出的三维可视化几何模型进行多种操作和任意方向的切片提取,对诊断具有参考价值,提高了诊疗方法的直观性、准确性和科学性.     

基于VTK的医学图像交互式三维测量技术研究

VTK是国外开发的集计算机图形.图像处理和可视化于一体的工具开发包,具有高度的灵活性、可移植性.提出一种使用VTK类库实现三维拾取的方法,能够将用户指定的屏幕坐标转化为三维物体坐标系下的空间坐标.最后通过牙齿模型的三维测量实验,证明这种方法具有良好的交互性和实时性.     

Hardware-assisted feature analysis and visualization of procedurally encoded multifield volumetric data

We take a new approach to interactive visualization and feature detection of large scalar, vector, and multifield computational fluid dynamics data sets that is also well suited for meshless CFD methods. Radial basis functions (RBFs) are used to procedurally encode both scattered and irregular gridded scalar data sets. The RBF encoding creates a complete, unified, functional representation of the scalar field throughout 3D space, independent of the underlying data topology, and eliminates the need for the original data grid during visualization. The capability of commodity PC graphics hardware to accelerate the reconstruction and rendering and to perform feature detection from this functional representation is a powerful tool for visualizing procedurally encoded volumes. Our RBF encoding and GPU-accelerated reconstruction, feature detection, and visualization tool provides a flexible system for visually exploring and analyzing large, structured, scattered, and unstructured scalar, vector, and multifield data sets at interactive rates on desktop PCs.     

Object-oriented visualization

Feature based techniques incorporated into standard visualization algorithms can greatly enhance the quantification and visualization of observed phenomena, as described in the article. The methods to isolate and recognize coherent 3D structures are analogous to 2D vision techniques. The overall goals are the same in both fields, namely, to interpret an image (data) and construct a model to describe it. Although the article uses data sets from numerical simulations of fluid flow, the concepts are applicable to other domains where scientists study the evolution and morphologies of 4D space time vector and scalar fields. More work is needed to explore complex features based upon domain specific knowledge and to define the parameters for classification and tracking. Sophisticated databases for storage and retrieval of feature based data sets are also an interesting area of study. The ultimate goal of visualization is to aid in the understanding and analysis of data. With faster parallel computers and more sophisticated laboratory equipment, information is being produced in ever greater amounts. This information must be presented to the scientist in a form suitable for cogent assimilation and manipulation. The article presents issues and algorithms for an object oriented approach to this problem and demonstrates its usefulness for visualization     

Three-Dimensional Vector Field Visualization Based on Tensor Decomposition

This paper presents a visualization method called the deformed cube for visualizing 3D velocity vector field.Based on the decomposition of the tensor which describes the changes of the velocity,it provides a technique for visualizing local flow.A deformed cube,a cube transformed by a tensor in a local coordinate frame,shows the local stretch,shear and rigid body rotation of the local flow corresponding to the decomposed component of the tensor.Users can interactively view the local deformation or any component of the changes.The animation of the deformed cube moving along a streamline achieves a more global impression of the flow field.This method is intended as a complement to global visualization methods.     

基于微分的增强型三维矢量场可视化

为提高3D矢量场可视化效果,提出了一种基于微分滤波的流线增强方法。首先对三维纹理进行线性卷积运算,生成具有空间相关性的卷积纹理;其次对卷积纹理进行分数阶微分滤波,增强流线之间强度对比;最后采用纹理映射体绘制技术实现三维矢量场可视化,并通过设计体绘制的传输函数来显示矢量场的内部结构。实验结果表明,该方法有效地增强了流线间的对比,使绘制的流线更加平滑,同时也有效地消除了卷积数据过多引起的紊乱与相互遮挡。     

车载PEPS低频自动标定系统

针对车载PEPS系统的低频发射场实测问题,设计了一套汽车电子设备电磁场自动标定系统.该系统控制三维机械臂实现自动行走将场强测试仪送到指定测试点并记录场强值,然后通过可视化技术实现了电磁场强的三维分布显示.设计的标定系统实现了对PEPS系统低频发射场高效而精确的标定,为深入研究PEPS系统电磁场分布特征奠定了基础.     

海洋标量数据多维多模式动态可视化系统设计实现

本文设计了基于地球直角坐标系和三维UTM坐标系的多维可视化系统。实现了两种坐标系的映射,并基于两种坐标系实现了海洋标量数据场的点过程、线过程、面过程同步可视化分析;通过内存映射技术实现了海量海洋标量数据的多维动态可视化。实验表明,系统能直观地表达海洋标量数据场在空间上的分布及在时间序列上的变化,可承载较大的数据量,满足实时性与交互性要求。     

An information-theoretic framework for flow visualization

The process of visualization can be seen as a visual communication channel where the input to the channel is the raw data, and the output is the result of a visualization algorithm. From this point of view, we can evaluate the effectiveness of visualization by measuring how much information in the original data is being communicated through the visual communication channel. In this paper, we present an information-theoretic framework for flow visualization with a special focus on streamline generation. In our framework, a vector field is modeled as a distribution of directions from which Shannon's entropy is used to measure the information content in the field. The effectiveness of the streamlines displayed in visualization can be measured by first constructing a new distribution of vectors derived from the existing streamlines, and then comparing this distribution with that of the original data set using the conditional entropy. The conditional entropy between these two distributions indicates how much information in the original data remains hidden after the selected streamlines are displayed. The quality of the visualization can be improved by progressively introducing new streamlines until the conditional entropy converges to a small value. We describe the key components of our framework with detailed analysis, and show that the framework can effectively visualize 2D and 3D flow data.     

Scalar field visualization via extraction of symmetric structures

Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.