BIGDATA: Modeling Simulation and Visulization for Medical Device Design

BIGDATA：医疗设备设计的建模仿真和可视化

• 批准号: 8655231
• 负责人: Daniel F Keefe
• 金额: $ 7.47万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8655231
• 关键词: Adopted; Area; Automobile Driving; Basic Science; Biological Sciences; Biomedical Engineering; Biomedical Technology; Biopsy; Cardiac; Complex; Computer Simulation; Computing Methodologies; Coupling; Data; Data Analyses; Data Set; Devices; Engineering; Future; Generations; Health; Human; Imagery; Medical Device; Medical Device Designs; Medical Imaging; Methods; Mission; National Institute of Biomedical Imaging and Bioengineering; Public Health; Research; Science; Scientist; Testing; Touch sensation; User-Computer Interface; Vacuum; Work; base; computerized tools; design; improved; insight; models and simulation; public health relevance; simulation; tool; virtual

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.

描述（由申请人提供）：该项目的长期目标是利用大数据为基于仿真的工程实现范式转变的未来，并通过特定应用来解决医疗设备设计中的挑战性问题来展示这一未来。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结合起来，这些工具不仅支持自动化数据分析，而且还强有力地利用我们人类自己的观察、触摸、探索和分析能力。对健康的潜在影响是深远的。通过采用以人为本的大数据科学方法，包括数据可视化和人机界面领域的重大新研究，这项工作不仅有望加速基础研究和发现，而且使医生、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成果。 有三个具体目标：（1）通过应用新的数据密集型设计工具来推进医疗器械工程； (2) 为基于仿真的工程开发一种创造性的尽可能直接的反演方法； (3) 将数据密集型虚拟设计与处理大数据的新有形工具相结合。这些目标与 NIBIB 的使命相关。通过开发先进的生物医学技术，可以从根本上提高科学家、工程师和医生在处理大量复杂的健康数据集时从数据转向洞察的能力，从而改善公共卫生。该研究将应用于两个重要的医疗设备工程问题：心脏导线的设计和真空辅助活检设备的设计。这项工作可能会给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预计将推广到许多其他大数据生物工程问题，为新一代数据密集型基于模拟的工程工具开辟道路，通过创建更安全、更有效的医疗设备来改善公共健康。