SLICER-LONI PIPELINE INTEGRATION ENVIRONMENT (SLIPIE)

神经照射和神经学临床数据的全部潜力，描述大脑结构和 功能，只有强大的神经成像，神经工程，神经信息学， 数据库和可视化工具集成在一个功能强大、可扩展和可移植的图形中 环境。我们将进一步开发、改进和集成用于图像的Slicer C++库 使用神经成像实验室(LONI)基于Java的管道环境进行分割、区域建模和可视化。这样的集成框架将使我们能够为我们的临床和研究合作者以及神经成像社区快速提供高效、可靠和及时的资源访问(例如，神经科学专业知识、分布式和网格计算、数据存储、管理和处理框架)。我们的首要目标是创建一个基础设施，确保为大规模脑图和神经成像研究提供高效的数据管理、可靠的处理和交互式数据可视化。这一核心基础设施的设计目的是提供在合并结构、功能、神经心理学和神经遗传学数据方面的独特专门知识，使在多模式数据建模方面几乎没有跨学科和(或)有限经验的研究人员能够使用。此外，所有原始和处理的成像数据、处理方案和可视化辅助工具将在合并后的几天内向公众提供，纳入新的集成Slicer-LONIPipeline集成环境(SLIPIE)。我们将把资源用于大幅提高我们有效执行大型最先进成像研究的能力，专注于为数据操作、过滤、分析和显示数据提供资源。

The full potential of neuroirnaging and neurological clinical data, describing brain structure and function, can be realized only if powerful neuroimaging, neuroengineering, neuroinformatics, database and visualization tools are integrated in a functional, extensible and portable graphic environment. We will further develop, improve and integrate the Slicer C++ libraries for image segmentation, region modeling and visualization with the Laboratory of Neuro Imaging (LONI) Javabased Pipeline environment. Such an integrated framework will permit us to provide efficient, robust and timely access to resources (e.g., neuroscientific expertise, distributed and Grid computing, data storage, management and processing framework) rapidly to our clinical and research collaborators and to the neuroimaging community. Our overriding goal is to create an infrastructure that will ensure efficient data management, reliable processing and interactive data visualization for large-scale brainmapping and neuroimaging studies. This core infrastructure will be designed to provide unique expertise in merging structural, functional, neuropsychological and neurogenetic data in a manner accessible to researchers who may have little interdisciplinary and/or limited experience in modeling multi-modal data. Furthermore, all raw and processed imaging data, processing protocols and visualization aids will be made available to the public within days of incorporation within the new integrated Slicer-LONIPipeline Integration Environment (SLIPIE). We will direct resources towards substantially increasing our capability of efficiently performing large state-of-the-art imaging studies in focusing on providing resources for data manipulation, filtering, analyzing and displaying data.