BIGDATA: Modeling Simulation and Visulization for Medical Device Design

描述（由申请人提供）：本项目的长期目标是通过大数据实现基于模拟的工程的范式转变，并通过医疗器械设计中具有挑战性问题的具体应用来证明这一未来。该方法是将当今生成的大量有价值的医学成像，物理模拟和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。对健康的潜在影响是深远的。通过采用以人为本的方法来进行大数据科学，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创造性思想家能够获得大数据科学的结果，这些人不一定具有计算方法的核心背景。 有三个具体目标：（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结合起来，以处理大数据。这些目标与尼加拉瓜国际商业银行的使命有关。公共卫生将通过开发先进的生物医学技术来改善，这些技术将从根本上提高科学家、工程师和医生在处理庞大、复杂的健康数据集时从数据转向洞察力的能力。该研究将应用于两个驱动医疗设备工程问题：心脏电极导线的设计和真空辅助活检设备的设计。这项工作可能会为这些设备带来新的设计见解。更重要的是，新的数据密集型 开发的设计方法和工具有望推广到许多其他大数据生物工程问题，为新一代基于数据密集型模拟的工程工具指明了道路，通过创造更安全、更有效的医疗设备来改善公共健康。

DESCRIPTION (provided by applicant): 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 valuable and 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. The potential impact on health is profound. 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 specific aims: (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. These aims are relevant to the mission of NIBIB. Public health will be improved by developing advanced biomedical technologies that radically improve the abilities of scientists, engineers, and doctors to move from data to insight as they work with vast, complex health datasets. The research will be applied to two driving medical device engineering problems: design of cardiac leads and design of vacuum assisted biopsy devices. The work is likely to result in new design insights for these devices. More importantly, the new data-intensive design methods and tools developed are expected to generalize to many other big data bioengineering problems, illuminating a path toward a new generation of data-intensive simulation-based engineering tools for improving public health by creating safer and more effective medical devices.