SCIENTIFIC VISUALIZATION

科学可视化

• 批准号: 7723091
• 负责人: CHRISTOPHER R. JOHNSON
• 金额: $ 18.85万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7723091
• 关键词: Algorithms; Architecture; Area; Arts; Behavior; Biomedical Computing; Computer Retrieval of Information on Scientific Projects Database; Computer software; Data; Data Set; Diffusion; Diffusion Magnetic Resonance Imaging; End Point; Engineering; Feedback; Funding; Goals; Grant; Image; Imagery; Institutes; Institution; Ion Transport; Measurement; Measures; Medicine; Methods; Performance; Purpose; Range; Research; Research Infrastructure; Research Personnel; Resources; Simulate; Software Tools; Source; Structure; Techniques; Technology; Time; Uncertainty; United States National Institutes of Health; Update; Visual; Visualization software; Work; base; bioimaging; biomedical scientist; clinical application; image visualization; improved; insight; prototype; research and development; scientific computing; simulation; size; tool; vector; voltage

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Scientific visualization is concerned with helping researchers explore measured or simulated data to gain insight into structures and relationships within the data. The impact of scientific visualization can be seen in all areas of science, medicine, and engineering. A central aim of this core is to bring cutting-edge visualization research and technology to biomedical scientists. The goals of the visualization technology core are to develop and then to implement advanced, efficient, high-performance algorithms and software for visualizing large, spatially distributed and/or time varying data sets. In order to achieve its full potential as an effective scientific tool, visualization must be not just the natural end point of the biomedical computing pipeline but a ubiquitous component of every step within that pipeline: it must enable to user to see the data from raw images to finished simulation and then to visualize the errors and uncertainties that arise from the measurements and computations applied to those data. In order to achieve these goals, we aim to greatly increase the breadth and sophistication of visualization technologies available for biomedical researchers, first by leveraging existing expertise within the Scientific Computing and Imaging Institute, then by carrying out new research directed at such areas as time-dependent image data, flow fields from bioelectric fields and other ion-transport behaviors, diffusion weighted MRI image sets, and data error/uncertainty and by combining such data types into intuitive, quantitative, interactive displays. Three primary visualization goals focus on both research and development: (1) to research new visualization techniques for biomedical applications, (2) to develop visualization tools and software for biomedical visualization based upon state- of-the-art visualization research developed within the Scientific Computing and Imaging Institute and elsewhere, and (3) to leverage third-party visualization software to take advantage of existing software. These aims both reflect the existing expertise of the center's investigators and include substantial components that have originated with the collaborative projects. Such close research ties between the center and its collaborators will improve the quality of the projects by broadening the sources of feedback and intellectual contributions and so help to maximize their impact on the field. Our research will include new work directed at such areas as multi-dimensional transfer function volume visualization of image data, multi-field visualization for bioelectric fields and other ion-transport behaviors, visualization of diffusion weighted MRI, and the creation of new visual representations for data error/uncertainty in experimental and computational data sets. In addition to our research goals, we aim to develop a set of powerful, interactive, quantitative, usable, and integrated visualization tools for biomedical scientists. The utility and impact of the research lie not only in the specific techniques we propose to develop and implement, but also in the way that these techniques will be integrated into BioPSE. Some of the techniques will be tuned to the specific needs of our collaborators or the particular research or clinical application, and many others, such as the multi-dimensional volume rendering, error and uncertainty visualization, and multi-field visualization, will also be appropriate for a broader range of applications. As part of the BioPSE, BioImage, ImageVis3D, TensorVis3D, and Seg3D infrastructures, these techniques will become immediately available to all users of the software for a range of related purposes. Below we give a brief summary of the center's visualization research and development goals: 1. Investigate new diffusion tensor visualization and analysis techniques. 2. Develop and harden state-of-the-art Scientific Computing and Imaging visualization research prototypes in scalar, vector, and tensor field visualization into robust BioPSE components. 3. Supply techniques that support extensive and flexible examination of the quantitative aspects of bioelectric field data, such as voltage gradients and isochrone velocities. 4. Update the architecture of our "BioImage" software package transitioning to the "ImageVis3d" software package. 5. Expand the capabilities of map3d , especially in the areas of time-dependent geometry and multiple-data visualization to meet the needs of the collaborators and other users, especially those in application areas outside of bioelectric fields. 6. Develop visual methods for comparisons of simulation results based upon the proposed visual representation of error and uncertainty research. 7. Examine new file structures to better accommodate the growing size and complexity of biomedical images Investigate methods for visualizing the error and uncertainty produced by measurement, simulation, and visualization techniques.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 科学可视化致力于帮助研究人员探索测量或模拟数据以深入了解 数据中的结构和关系。科学可视化的影响遍及科学的各个领域， 医学、工程学。 该核心的中心目标是将尖端的可视化研究和技术引入 生物医学科学家。 可视化技术核心的目标是开发并实施先进的、 用于可视化大型、空间分布和/或时变数据的高效、高性能算法和软件 套。 为了充分发挥其作为有效科学工具的潜力，可视化不能只是自然的结果 生物医学计算管道的一个点，但该管道中每个步骤的普遍组成部分：它必须启用 让用户查看从原始图像到完成的模拟的数据，然后可视化其中的错误和不确定性 由应用于这些数据的测量和计算产生。 为了实现这些目标，我们的目标是大大增加可视化技术的广度和复杂性 供生物医学研究人员使用，首先利用科学计算和成像领域的现有专业知识 研究所，然后通过针对时间相关图像数据、流场等领域开展新研究 生物电场和其他离子传输行为、扩散加权 MRI 图像集以及数据误差/不确定性 将这些数据类型组合成直观、定量、交互式的显示。 研究和开发的三个主要可视化目标：（1）研究新的可视化技术 对于生物医学应用，（2）开发基于状态的生物医学可视化可视化工具和软件 在科学计算和成像研究所和其他地方开发的最先进的可视化研究，以及 (3)利用第三方可视化软件，充分利用现有软件。这些目标都反映了 该中心研究人员现有的专业知识，包括源自该中心的重要组成部分 合作项目。 该中心与其合作者之间如此密切的研究联系将提高研究的质量 项目通过扩大反馈和智力贡献的来源，从而有助于最大限度地发挥其对 领域。 我们的研究将包括针对多维传递函数体积等领域的新工作 图像数据可视化、生物电场和其他离子传输行为的多场可视化、可视化 扩散加权 MRI 的研究，以及为实验和实验中的数据错误/不确定性创建新的视觉表示 计算数据集。 除了我们的研究目标之外，我们的目标是开发一套强大的、交互式的、定量的、可用的和集成的 生物医学科学家的可视化工具。研究的效用和影响不仅仅在于具体技术 我们建议开发和实施，但也以将这些技术集成到 BioPSE 中的方式。一些 这些技术将根据我们合作者的具体需求或特定的研究或临床应用进行调整， 以及许多其他，例如多维体绘制、误差和不确定性可视化以及多场 可视化，也将适用于更广泛的应用。作为 BioPSE、BioImage、ImageVis3D 的一部分， TensorVis3D 和 Seg3D 基础设施，这些技术将立即可供该软件的所有用户使用 用于一系列相关目的。下面我们简单总结一下中心的可视化研发情况 目标： 1. 研究新的扩散张量可视化和分析技术。 2. 开发并强化最先进的标量科学计算和成像可视化研究原型， 矢量和张量场可视化为强大的 BioPSE 组件。 3. 提供支持对生物电场数据的定量方面进行广泛和灵活检查的技术， 例如电压梯度和等时线速度。 4. 更新“BioImage”软件包的架构，过渡到“ImageVis3d”软件包。 5. 扩展map3d的功能，特别是在时间相关几何和多数据可视化领域 满足合作者和其他用户的需求，特别是生物电领域以外的应用领域的需求。 6. 根据所提出的误差视觉表示，开发用于比较模拟结果的视觉方法 和不确定性研究。 7. 检查新的文件结构，以更好地适应生物医学图像不断增长的尺寸和复杂性 研究将测量、模拟和可视化产生的误差和不确定性可视化的方法 技术。