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.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 科学可视化涉及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。科学可视化的影响可以在科学的所有领域中看到 医学和工程。 该核心的主要目的是将尖端的可视化研究和技术带到 生物医学科学家。 可视化技术核心的目标是开发然后实施高级， 高效，高性能算法和用于可视化大型，空间分布和/或时间变化数据的软件 套。 为了充分发挥其作为有效科学工具的全部潜力，可视化不仅必须是自然目的 生物医学计算管道的点是该管道中每个步骤的无处不在组成部分：它必须启用 向用户查看从原始图像到完成的模拟的数据，然后可视化错误和不确定性 来自应用于这些数据的测量和计算。 为了实现这些目标，我们旨在大大提高可视化技术的广度和复杂性 可用于生物医学研究人员，首先利用科学计算和成像中的现有专业知识 研究所，然后进行针对时间相关图像数据等领域的新研究，从 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/不确定性以及通过 将这些数据类型组合为直观，定量，交互式显示。 三个主要的可视化目标都集中在研究和开发上：（1）研究新的可视化技术 （2）为生物医学应用开发可视化工具和软件，以基于状态 - 科学计算和成像研究所以及其他地方开发的现象可视化研究，以及 （3）利用第三方可视化软件来利用现有软件。这些目标都反映了 该中心调查人员的现有专业知识，包括源自该中心的大量组成部分 协作项目。 中心与其合作者之间的这种紧密研究关系将提高 通过扩大反馈和智力贡献的来源来进行项目，从而帮助他们最大化其对 领域。 我们的研究将包括针对多维传输功能量的领域的新工作 图像数据的可视化，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，并创建实验和实验性数据误差/不确定性的新视觉表示形式 计算数据集。 除了我们的研究目标外，我们还旨在开发一套强大的，互动的，定量的，可用的和综合的 生物医学科学家的可视化工具。研究的实用性和影响不仅在于特定技术 我们建议开发和实施这些技术将这些技术集成到Biopse中。其中一些 这些技术将根据我们的合作者的特定需求或特定的研究或临床应用， 还有许多其他，例如多维体积渲染，错误和不确定性可视化以及多场 可视化，也适用于更广泛的应用。作为Biopse的一部分，生物图像，ImageVis3d， Tensorvis3D和SEG3D基础架构，这些技术将立即用于软件的所有用户 用于一系列相关目的。下面我们简要摘要该中心的可视化研究和开发 目标： 1。研究新的扩散张量可视化和分析技术。 2。在标量中开发和硬化最先进的科学计算和成像可视化研究原型， 向量和张量场可视化成稳健的Biopse组件。 3。支持对生物电场数据定量方面的广泛和灵活检查的供应技术， 例如电压梯度和异隆速度。 4。更新我们的“生物图像”软件包的体系结构，将其转换为“ ImageVis3d”软件包。 5。扩展MAP3D的功能，尤其是在时间依赖性几何和多数据可视化的领域 为了满足合作者和其他用户的需求，尤其是在生物电场以外的应用领域的需求。 6。根据提出的误差的视觉表示，开发可视化方法，以比较模拟结果 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的增长和复杂性 研究通过测量，仿真和可视化产生的误差和不确定性的方法 技术。