MRI: Acquisition of a Hybrid System and Research Infrastructure for Large-Scale Integration of Biomedical Data
MRI: Acquisition of a Hybrid System and Research Infrastructure for Large-Scale Integration of Biomedical Data
批准号:
0521527
负责人:
George Zouridakis
金额:
$90.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-08-01 至 2010-07-31
中文摘要
该项目专注于提取信息和集成异构信息系统的方法和体系结构,以及挖掘实时收集的多媒体/多模态数据,为在生物信号分析和生物计算领域具有共同兴趣的大型用户社区提供服务。该基础设施是一个部分基于Windows和部分基于unix的混合系统,旨在实时获取、分析、集成、安全存储和可视化从实验对象获得的大量多模态/多传感器数据。这些数据是由目前存在于实验室的传感系统在当地产生的,包括热像仪、3D立体摄像机和大脑活动扫描仪。该系统能够整合远程合作机构收集的数据,可能包括MRI和CT扫描或实时神经生理活动。该设施是对现有系统的补充,现有的高性能计算机主要用于数字处理,旨在长时间不间断地运行。目前,这些研究人员有独立的实验室,每个实验室都专门研究不同的图像模式。该提案旨在统一这些实验室,扩展模式的范围,并增加计算和可视化资源。该项目依靠跨学科专家团队整合现有的最佳工具和信息技术实践,并开发针对现实世界生物医学应用的共同需求的软件工具,解决了生物医学数据收集日益复杂的需求,以及计算生物科学今天所依赖的数字信息的分析和分发。该基础设施支持功能成像(人类学习的计算跟踪)、热成像和光学成像以及分布式计算等正在进行的项目。更广泛的影响:这项工作将显著推动计算生物医学和生物工程的发展,并为目前正在研究的复杂问题提供答案。它可能会在人机界面和基于生物识别的安全领域带来新的应用。这些设施向学术界和工业界的研究人员开放,作为科学家的研究和培训场所,通过为学生提供实践经验,直接影响教育活动。
英文摘要
This project, focusing on methodologies and architectures for extracting information and integrating heterogeneous information systems, and mining multimedia/multimodality data collected in real time, services a large community of users with common interests in the areas of biosignal analysis and biocomputation. The infrastructure is a hybrid partly Windows- and partly Unix-based system, designed to acquire, analyze, integrate, securely store, and visualize large volumes of multimodal/multisensor data obtained from an experimental subject, all in real time. The data are generated locally by sensing systems that currently exist in the laboratories, and include thermal cameras, 3D stereo video cameras, and brain activity scanners. Capable of integrating data collected at remote collaborating institutions, the system may include MRI and CT scans or live neurophysiological activity. The facility compliments the systems already available where the existing high-performance computers, primarily devoted to number crunching, are intended to run for a long time without interruption. Currently, these researchers have separate labs, each specializing in a different image modality. The proposal seeks to unify these labs, extend the range of modalities, and add computational and visualization resources. Relying on an interdisciplinary team of experts to integrate the best existing tools and practice of information technology, and to develop software tools specific to the common needs of real-world biomedical applications, the project addresses the needs of the ever-increasing complexity of biomedical data collection, and analysis and distribution of digital information upon which computational biosciences are dependent today. The infrastructure supports ongoing projects in-Functional imaging (computational tracking of human learning),-Thermal and Optical Imaging, and-Distributed computing.Broader Impact: This work should significantly advance the state-of-the-art in computational biomedicine and bioengineering and should provide answers to complex problems currently under investigation. It may lead to new applications in the areas of human-computer interface and biometrics-based security. The facilities, opened to researchers from academia and industry, serve as research and training grounds for scientists, impacting directly the educational activities by providing hand-on experience to students.
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