BIGDATA: Small: DA: Coupling Data-Intensive Modeling, Simulation, and Visualization with Human Facilities for Design: Applications to Next-Generation Medical Device Prototyping

大数据：小：DA：将数据密集型建模、仿真和可视化与人类设计设施相结合：在下一代医疗设备原型设计中的应用

• 批准号: 1251069
• 负责人: Daniel Keefe
• 金额: $ 50.1万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1251069&HistoricalAwards=false
• 关键词: BIGDATA; Small; DA; Coupling; Data

The goal of this research project is to transform the way that scientists, engineers, and medical professionals make use of big data in order to further science, solve challenging problems in medical device engineering, and, ultimately, improve the nation's health. The approach makes use of big data from medical imaging, supercomputer simulation, and other sources. These exciting datasets are just now becoming available and have great potential to revolutionize science, engineering, and medicine. Unfortunately, scientists today cannot take full advantage of these data because they lack the appropriate tools to work with such large and complex datasets. This research addresses that problem by creating new computer graphics-based data visualization tools and coupling these with novel human-computer interfaces that specifically support data-driven engineering design. The new style of interactive visual computing that these tools provide can be especially powerful for supporting the human process of design. Thus, an anticipated major scientific result of the work is a new approach for supporting creative human-in-the-loop tasks when working with big data. The impact of this new approach is demonstrated through a series of applications to medical device design problems, such as designing improved breast biopsy devices and cardiac leads.The long-term objectives of this project are to enable a paradigm-shifting future for simulation-based engineering with big data and to demonstrate this future through specific applications to challenging problems in medical device design. The approach is to couple the intense amounts of medical imaging, physical simulation, and other life sciences data that are generated today with new computational tools that not only support automated data analysis but also powerfully leverage our own human capabilities to see, touch, explore, and analyze. By adopting a human-centric approach to big data science, including significant new research in the areas of data visualization and human-computer interfaces, the work is expected to not only accelerate basic research and discovery but also make the results of big data science accessible to doctors, medical device engineers, and countless other creative thinkers who do not necessarily have a core background in computational methods. There are three main thrusts to the research: (1) Advancing medical device engineering through applications of new data-intensive design tools; (2) Developing a creative new as-direct-as-possible inverse method for simulation-based engineering; and (3) Coupling data-intensive virtual design with new tangible tools for working with big data.

该研究项目的目标是改变科学家、工程师和医疗专业人员利用大数据的方式，以进一步推动科学发展，解决医疗器械工程中的挑战性问题，并最终改善国民健康。 该方法利用了来自医学成像、超级计算机模拟和其他来源的大数据。 这些令人兴奋的数据集现在才开始可用，并具有巨大的潜力来彻底改变科学，工程和医学。 不幸的是，今天的科学家无法充分利用这些数据，因为他们缺乏适当的工具来处理如此庞大而复杂的数据集。 这项研究通过创建新的基于计算机图形的数据可视化工具，并将这些工具与专门支持数据驱动工程设计的新型人机界面相结合来解决这个问题。 这些工具提供的新型交互式视觉计算对于支持人类的设计过程尤其强大。 因此，这项工作的一个预期的主要科学成果是在处理大数据时支持创造性人在回路任务的新方法。这一新方法的影响通过一系列医疗器械设计问题的应用得到了证明，例如设计改进的乳腺活检设备和心脏电极导线。该项目的长期目标是为基于模拟的工程与大数据实现范式转变的未来，并通过医疗器械设计中具有挑战性的问题的具体应用来证明这一未来。 该方法是将大量的医学成像，物理模拟和今天生成的其他生命科学数据与新的计算工具相结合，这些工具不仅支持自动化数据分析，而且还可以有效地利用我们自己的人类能力来观察，触摸，探索和分析。 通过采用以人为本的方法来研究大数据科学，包括在数据可视化和人机界面领域的重要新研究，这项工作不仅有望加速基础研究和发现，而且还将使医生、医疗设备工程师和无数其他不一定具有计算方法核心背景的创造性思想家能够获得大数据科学的结果。 该研究有三个主要目标：（1）通过应用新的数据密集型设计工具推进医疗器械工程;（2）为基于仿真的工程开发一种创造性的新的尽可能直接的逆向方法;（3）将数据密集型虚拟设计与新的有形工具相结合，以处理大数据。