SLICER-LONI PIPELINE INTEGRATION ENVIRONMENT (SLIPIE)

神经影像学和神经学临床数据的全部潜力，描述大脑结构和 功能，只有在强大的神经成像，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Slicer C++图像库 分割，区域建模和可视化与神经成像实验室（LONI）基于Java的管道环境。这样一个综合框架将使我们能够有效、有力和及时地获得资源（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）迅速提供给我们的临床和研究合作者以及神经影像学界。我们的首要目标是创建一个基础设施，以确保大规模脑成像和神经成像研究的有效数据管理，可靠的处理和交互式数据可视化。这一核心基础设施将被设计为提供独特的专业知识，在合并结构，功能，神经心理学和神经遗传学数据的方式访问的研究人员谁可能有很少的跨学科和/或有限的经验，在建模多模态数据。此外，所有原始和处理后的成像数据、处理协议和可视化辅助工具将在纳入新的集成切片机-LONIPipeline集成环境（SLIPIE）后的几天内向公众提供。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，重点是为数据操作、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.