MRI: Acquisition of a Hybrid System and Research Infrastructure for Large-Scale Integration of Biomedical Data

该项目侧重于提取信息和整合不同类型信息系统的方法和体系结构，并挖掘实时收集的多媒体/多模式数据，为在生物信号分析和生物计算领域具有共同兴趣的广大用户群体提供服务。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、安全存储从实验对象获得的大量多模式/多传感器数据并将其可视化。这些数据是由实验室目前存在的传感系统在本地生成的，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协作机构收集的数据，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，这些研究人员有不同的实验室，每个实验室专门研究一种不同的图像模式。该提案寻求统一这些实验室，扩大模式的范围，并增加计算和可视化资源。该项目依靠一个跨学科的专家团队来整合现有的最佳信息技术工具和实践，并针对现实世界生物医学应用程序的共同需求开发软件工具，以满足当今计算生物科学所依赖的日益复杂的生物医学数据收集、分析和数字信息分发的需求。该基础设施支持正在进行的功能成像(人类学习的计算跟踪)、热成像和光学成像以及分布式计算的项目。广泛影响：这项工作应该会显著推进计算生物医学和生物工程的最新水平，并应该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地，通过向学生提供实践经验直接影响教育活动。

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.