VISUALIZATION

可视化

• 批准号: 8363709
• 负责人: CHRISTOPHER R. JOHNSON
• 金额: $ 19.24万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8363709
• 关键词: Address; Algorithms; Biological; Biomedical Computing; Client; Collaborations; Computer Simulation; Computer software; Computers; Data; Data Analyses; Data Set; Engineering; Funding; Goals; Grant; Image; Imagery; Institutes; Measures; Medicine; Methods; Modality; Modeling; National Center for Research Resources; Performance; Principal Investigator; Reproducibility; Research; Research Infrastructure; Research Personnel; Resolution; Resources; Science; Scientist; Simulate; Site; Source; Stream; Surface; System; Techniques; Technology; Testing; Time; United States National Institutes of Health; Vision; biomedical scientist; clinical decision-making; comparative; computerized data processing; cost; data acquisition; data management; design; insight; interest; remote sensing; research and development; research study; simulation; skills; trend

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Background: The Visualization TRD helps researchers gain insight into measured or simulated data by providing cutting-edge visualization research and software to biomedical scientists. The goals of the Center's visualization technology core are to develop and then implement advanced, high-performance algorithms and software for visualizing large, spatially distributed and/or time-varying data sets. In order to achieve our goals, we propose to both create new algorithms and software and to leverage existing visualization expertise within the SCI Institute. Rationale: Computers are extensively used throughout science, engineering, and medicine. Advances in computational geometric modeling, imaging, and simulation allow researchers to build and test models of increasing complexity, generating unprecedented amounts of data. The Visualization TRD reflects an explicit effort to match the needs or interests of the DBPs in this project and the field at large with the unique technical skills and capabilities of researchers in the SCI Institute. These aims also demonstrate an integrated vision, cutting across the different TRDs in this proposal, for a pipeline where scientists start with measured data of various modalities and produce quantitative results that help them make clinical decisions or gain new biological insights. Questions: In many ways, science is becoming a data management problem. The trend toward data- intensive science can be attributed to advances in data acquisition technology: highthroughput lab techniques, remote sensing platforms, and, in the case of in silico experiments, high-resolution computational modeling. Unfortunately, the infrastructure for conducting data-intensive experiments and simulations has not kept pace with our collective ability to gather and create large-scale data, leading to an unprecedented situation: Data analysis and visualization are now a bottleneck to scientific discovery. Design & Methods: The Visualization TRD aims address the following important research and development objectives: (1) Large-scale volume rendering and manipulation, and interactive visualization of one or multiple high-resolution, time-dependent data sets; (2) Design and realization of multi-site collaboration through progressive streaming datastructures, interactive volume, and surface annotation algorithms, mobile clients, and task-specific user interfaces; (3) Research and development of multi-scale visualization techniques for large-scale high-resolution volumes in non-cartesian representations; (4) Enable the efficient use of GPUs and multi-core processors for large-scale visualization and data processing; and (5) Leveraging our significant expertise for provenance, reproducibility, and comparative visualization via the VisTrails system.

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 背景： 可视化TRD通过以下方式帮助研究人员深入了解测量或模拟的数据 为生物医学科学家提供尖端的可视化研究和软件。这个 该中心可视化技术核心的目标是开发并实施 先进、高性能的算法和软件，用于可视化大型空间 分布式和/或时变数据集。为了实现我们的目标，我们提议 两者都创建了新的算法和软件，并利用现有的可视化专业知识 在SCI研究所内。 基本原理： 计算机广泛应用于科学、工程和医学领域。预付款 在计算几何建模中，成像和模拟允许研究人员建立 并测试日益复杂的模型，生成前所未有的数据量。这个 可视化TRD反映了在以下方面与DBP的需求或兴趣相匹配的明确努力 该项目和整个领域具有独特的技术技能和能力 SCI研究所的研究人员。这些目标也展示了一个综合的愿景， 在这项提案中，跨越不同的TRD，为科学家们开始的管道 各种医疗模式的测量数据，并产生有助于它们的量化结果 做出临床决策或获得新的生物学见解。 问题： 在很多方面，科学正在成为一个数据管理问题。数据的趋势是- 密集的科学可以归因于数据采集技术的进步： 高通量实验室技术、遥感平台，就硅胶技术而言 实验，高分辨率的计算建模。不幸的是，基础设施 进行数据密集型实验和模拟的速度跟不上我们的 收集和创建大规模数据的集体能力，导致前所未有的 情况：数据分析和可视化现在是科学发现的瓶颈。 设计与方法： 可视化TRD的目标是解决以下重要研究和开发 目标：(1)大规模的体绘制和操纵，以及交互 一个或多个高分辨率、依赖时间的数据集的可视化；(2)设计和 通过渐进的流数据结构实现多站点协作， 交互式体积、曲面注记算法、移动客户端和特定于任务的 用户界面；(3)多尺度可视化技术研究与开发 以非笛卡尔表示的大规模高分辨率体积；(4)使 高效使用GPU和多核处理器实现大规模可视化和数据 加工；以及(5)利用我们在来源、再现性、 并通过VisTrails系统进行对比可视化。