Tools for Analyzing Cortical Structure and Connectivity

描述（由申请人提供）：通过融合来自多个成像模态的信息，多模态成像可以提供比单独使用的各个模态大得多的生物信息内容和检测能力。尽管多模态成像框架的前景，多个成像模态的集成在实践中往往受到阻碍的需要，集成先进的软件应用程序，这是不为互操作性而设计的。例如，集成独立的分析环境需要协调不同的坐标系统，协调质量保证目标，并集成开发人员的知识。虽然多模态成像软件工程的独特挑战在该领域得到了认可，但尚未开发出具体的软件方法来解决这些挑战。在这项补助金中，我们建议开发一套多模态脑成像的软件工程方法。该项目包括两个软件工程目标和一个驱动生物学目标：（1）整合和现代化解剖分析包（Free Surfer）和扩散张量分析包（Free Diffusion）。(2)（3）应用多模态框架整合高分辨率结构MRI和高角分辨率弥散MRI。多模态结构扩散MRI框架将被用来研究老年大脑中灰质皮质厚度和白色物质微结构完整性之间的关系。这种方法将使我们能够研究衰老大脑的皮质结构和远程连接架构之间的相关性，这是衰老生理学中的一个关键问题。开发一个强大的软件工程框架，集成多个图像分析环境的承诺，显着加快多模态脑成像方法的发展，并允许更丰富的利用多模态框架。

DESCRIPTION (provided by applicant): By fusing information from multiple imaging modalities, multimodal imaging can provide substantially greater biological information content and detection power than the individual modalities employed in isolation. Despite the promise of the multimodal imaging framework, integration of multiple imaging modalities is often hindered in practice by the need to integrate advanced software applications which were not designed for interoperability. For example, integration of separate analysis environments requires reconciling different coordinate systems, harmonizing quality assurance goals, and integrating developer knowledge. While the unique challenges of software engineering for multimodal imaging are recognized in the field, no specific software methodology has been developed yet to address these challenges. In this grant, we propose to develop a set of software engineering methods for multimodality brain imaging. The project consists of two software engineering aims, and a driving biological aim: (1) integrate and modernize an anatomical analysis package (Free Surfer) and a diffusion tensor analysis package (Free Diffusion). (2) develop software methods for automatic failure detection in multimodal imaging; and (3) apply multimodal framework to integrate high resolution structural MRI and high angular resolution diffusion MRI. The multimodal structural-diffusion MRI framework will be employed to investigate the relationship between gray matter cortical thickness and the white matter microstructural integrity in the aging brain. This approach will allow us to investigate the correlation between the cortical structure and long-range connectional architecture of the aging brain, a key question in the physiology of aging. Development of a robust software engineering framework for integrating multiple image analysis environments promises to significantly accelerate the development of multimodal brain imaging methods and allow for richer exploitation of the multimodal framework.