BRAINS Morphology and Image Analysis

大脑计划是在过去的15年里发展起来的，研究精神病学和神经学。 全球有350多个网站下载了该软件。它为分析提供了广泛的工具 包括空间归一化、图像配准、组织分类、自动化的脑形态 结构识别、表面生成、扩散张量分析和化学位移成像部分 音量修正。目前，Brains软件是37个Active的主要图像处理包 爱荷华大学的助学金和待定助学金，以及外部站点的46个助学金。该软件包含一个可靠的 为脑形态分析提供了有效的图像处理流水线。在本提案中，我们将完全自动化 这条管道允许对大规模成像研究进行快速分析。这项工作将建立在 将ITK工具包整合到Brains软件中。我们建议简化维护， 加强开发，并让更多的用户可以使用大脑。维护和维护 代码强化任务将利用已开发的几个开源工具(CMake和Dart 作为ITK项目的一部分。这将允许代码审查过程向程序的用户开放。这个 目前的Brains用户界面将被Fltk取代，提供跨Windows的本机用户界面， 基于Macintosh和Unix/Linux的平台。评估大脑和其他几个神经成像软件 应用程序由思维研究所收集的独特的多中心数据集将用于 测量站点内和站点间的可靠性以及这些工具的有效性。

The BRAINS program has been developed over the past fifteen years to study psychiatric and neurological disorders and has been downloaded by over 350 sites worldwide. It provides extensive tools for the analysis of brain morphology including spatial normalization, image co-registration, tissue classification, automated structure identification, surface generation, diffusion tensor analysis, and chemical shift imaging partial volume correction. Currently, the BRAINS software is the primary image processing package for 37 active grants and pending grants at The University of Iowa and 46 at outside sites. The software contains a reliable and valid image processing pipeline for analyzing brain morphology. In this proposal we will fully automate this pipeline allowing for large scale imaging studies to be rapidly analyzed. This work will build upon the integration of the ITK toolkit into the BRAINS software. We are proposing to streamline maintenance, enhance development, and make BRAINS available to a wider audience of users. The maintenance and code hardening tasks will leverage several open source tools (CMake and DART) that have been developed as part of the ITK project. This will allow the code review process to be open to users of the program. The current BRAINS user interface will be replaced with FLTK providing a native user interface across Windows, Macintosh and Unix/Linux based platforms. To evaluate BRAINS and several other neuroimaging software applications a unique multi-center dataset that has been collected by the MIND Institute will be used to measure intra- and inter-site reliability as well as validity of these tools.