Resource Development for the Java Image Science Toolkit

描述（由申请人提供）：医学成像数据的收集量如此之大，以至于尽管可能已经存在用于执行许多程序的公开可用工具，但执行适当的处理步骤通常是一项挑战。在集成来自各种平台的软件时，一个自动处理格式和兼容性问题的工具是必不可少的。神经成像社区受益于几个优秀的流水线工具和图像处理库。这些环境为最终用户提供了处理和可视化大规模数据集的系统。虽然在一个成功的系统中所需要的特性（例如，网格处理、方框图）方面已经有了实质性的收敛，但Java图像科学工具包（JIST）独特地解决了重要的挑战。跨平台编译和部署是出了名的困难，但是JIST是基于Java编程语言（Sun Microsystems, Santa Clara， CA）的，它本质上是跨平台的，能够在几乎任何平台上运行。到目前为止，还没有其他管道软件原生使用Java的神经成像图像处理库。JIST支持一种独特的“一次写入，多次运行”的开发风格：程序员只需要编写代码的核心部分，用户可以通过许多不同的方式访问该功能（例如，在框图中，作为插件，从命令行，从Matlab中，在网格上，等等）。因此，JIST提供了从原型到基于集群的并行处理的无缝开发路径。拟议的研究和开发工作将显著提高JIST框架的互操作性和可采用性，以增强更广泛的神经成像研究社区的采用。具体来说，这项工作将(1)增强开发人员在协作开发中监视和验证模块化例程的能力，(2)通过交互式可视化能力和详细的文档提高可用性。选择这些目标是为了指导针对现有JIST用户的具体关注的开发工作。该提案的主要假设是，通过解决当前JIST用户的具体问题，该平台将更容易被更广泛的神经影像学社区使用。反过来，JIST将为临床研究的进步提供更重要的贡献。这些开发将简化学习曲线，并为开发人员和用户提供更直观和响应更快的体验。用户将能够更容易地利用JIST中已有的大量图像分析功能，并从改进的高级特性的可访问性中受益。

DESCRIPTION (provided by applicant): Medical imaging data can be gathered in such vast quantities that it is often a challenge to carry out appropriate processing steps despite publicly available tools that might already exist for carrying out many of the procedures. A tool that automatically handles formatting and compatibility issues while integrating software from a variety of platforms is essential. The neuroimaging community benefits from several, excellent pipeline tools and image processing libraries. These environments provide end-users with systems to process and visualize large-scale datasets. While there has been substantial convergence in terms of the desirable features in a successful system (e.g., grid processing, block diagrams), the Java Image Science Toolkit (JIST) uniquely address important challenges. Cross-platform compilation and deployment are notoriously difficult, but JIST is based on the Java programming language (Sun Microsystems, Santa Clara, CA), which is inherently cross-platform and able to run on almost any platform. To date, no other pipeline software has made native use of neuroimaging image processing libraries with Java. JIST enables a unique flavor of "write-once, run many" development: programmers need only write a core section of code and users can access this functionality in many different ways (e.g., within block diagram, as a plugin, from the command line, from within Matlab, on a grid, etc.). Thus, JIST provide a seamless development path from prototype to cluster-based parallel processing. The proposed research and development effort will significantly improve the interoperability and adoptability of the JIST framework to enhance adoption by the broader neuroimaging research community. Specifically, this work will (1) enhance developers' ability to monitor and validate modular routines in collaborative development and (2) improve the usability through interactive visualization capabilities and detailed documentation. These aims have been chosen to direct development efforts at the specific concerns of existing JIST users. The primary hypothesis of this proposal is that by addressing the specific concerns of current JIST users, the platform will be made more accessible to the broader neuroimaging community. In turn, JIST will provide a more significant contribution toward advances in clinical research. These developments will ease the learning curve and provide more intuitive and responsive experiences for both developers and users. Users will be able to more readily leverage the substantial image analysis capabilities already available within JIST and benefit from improved accessibility of advanced features. PUBLIC HEALTH RELEVANCE: The proposed research improves the interoperability and adoptability of the Java Image Science Toolkit (JIST) resource using the Neuroimaging Informatics Tools and Resources Clearinghouse infrastructure. This effort will provide a more intuitive and responsive experience for both developers and users through an improved user interface and an automated algorithm validation and testing system. The end result will be that clinical investigators and image scientists will be able to more readily leverage the substantial analysis capabilities already available within JIST.