DISSEMINATION OF CROSS-PLATFORM SOFTWARE FOR ARTIFACT DETECTION AND REGION OF INT

描述(由申请人提供)：该项目的总体目标是传播软件，以提高功能磁共振成像(FMRI)数据分析的质量和一致性。其目标是增强、记录和公开用于伪影检测、统计感兴趣区域分析和功能磁共振数据可视化的软件。更好的质量控制方法和统计方法将产生更可信和可重复的结果，因此应该会导致更快的生物医学发现，并可能降低运行功能磁共振研究的成本。从软件工程的角度来看，目标是提供一个设计良好、跨平台、可扩展、直观且易于使用的软件。将增强、整合和分发现有的两个基于MatLab的软件包：人工产物检测工具(ART)和分割成像数据的感兴趣区域分析(RAPID)软件(Nieto-Castanon等人，2003年)。为了实现互操作性，集成的软件将从MatLab转换为C/C++，并将提供包装器，以供从其他语言如Python、Java、TCL/Tk和MatLab使用该软件。将为在某些功能分析流(FMRIB软件库，FSL，Smith等人，2004，统计参数映射，SPM，Friston 2003，Freesurfer Functional Analyst Stream，FSFAST，Tsao等人，2003和在Python，NiPy中的神经成像)中使用该软件创建定制模块，并将提供支持，以将该软件嵌入其他分析流中。为了实现传播，该软件将在进行功能磁共振研究的几个实验室进行Beta测试，并将通过神经成像信息学工具和资源信息中心(NITRC)网站进行维护和支持。该项目将分三个阶段进行：(1)整合和发布基于MatLab的软件；(2)将软件转换为C/C++框架；(3)传播和支持，以确保神经成像界的广泛使用。在整个项目中，我们将通过NITRC网站与神经成像社区接触，特别是与承诺对该软件进行Beta测试的几个实验室进行互动。我们将依靠社区反馈来提高软件的可用性。与公共卫生相关：拟议的项目旨在传播软件，用于复杂的统计分析(Nieto-Castanon等人，2003年)和功能磁共振成像(FMRI)数据的质量控制。提供这些工具应该使功能磁共振技术的用户能够产生更详细、一致和可靠的结果。这将导致更好地了解大脑是如何工作的，从而直接影响诊断和治疗神经疾病的方法。

DESCRIPTION (provided by applicant): The general aim of this project is to disseminate software that will enhance the quality and consistency of analysis of functional magnetic resonance imaging (fMRI) data. The goal is to enhance, document and make publicly available software for artifact detection, statistical region-of-interest analysis and visualization of fMRI data. Better quality control methods and statistical methods will generate more credible and repeatable results, which should therefore lead to faster biomedical discoveries and to potential reduction in the cost of running fMRI studies. From a software engineering standpoint, the goal is to offer a well-designed, cross- platform, extensible software that is intuitive and easy to use. Two existing MATLAB-based software packages will be enhanced, integrated and distributed: the ARtifact detection Tools (ART) and the Region of Interest Analysis of Parcellated Imaging Data (RAPID) software (Nieto-Castanon et al., 2003). To achieve interoperability, the integrated software will be converted from MATLAB to C/C++ and wrappers will be provided for use of this software from other languages such as Python, Java, Tcl/Tk and MATLAB. Custom modules will be created for use of this software within some functional analysis streams (FMRIB Software Library, FSL, Smith et al., 2004, Statistical Parametric Mapping, SPM, Friston 2003, FreeSurfer Functional Analysis STream, FSFAST, Tsao et al., 2003 and Neuroimaging in Python, NiPy), and support will be provided to embed the software in other analysis streams. To achieve dissemination, the software will be beta-tested at several laboratories doing fMRI research and will be maintained and supported through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) website. The project will be carried out in three phases: (1) Integration and release of MATLAB-based software; (2) Conversion of the software to a C/C++ framework; and (3) Dissemination and support to ensure widespread use by the neuroimaging community. Throughout the project we will engage with the neuroimaging community through the NITRC website and, in particular, interact with the several laboratories that have committed to beta-testing the software. We will rely on community feedback to improve usability of the software. PUBLIC HEALTH RELEVANCE: The proposed project aims to disseminate software for sophisticated statistical analyses (Nieto-Castanon et al., 2003) and quality control of functional magnetic resonance imaging (fMRI) data. Providing these tools should enable users of fMRI technology to produce more detailed, consistent and reliable results. This will lead to better understanding of how the brain works and thereby directly impact approaches to diagnosing and treating neurological disorders.