SPATIALLY ORIENTED DATABASE FOR DIGITAL BRAIN IMAGES

描述：(申请人摘要) 这个项目的总体目标是开发一种数字大脑图像。 集成图像处理和可视化的数据库(辫子) 能力，空间和临床数据的统计分析，以及 数字脑图集的管理，所有这些都可由普通用户访问 界面。这些组件的集成是Braid成功的关键 在推导出结构和结构之间具有临床意义的关联时 人脑的功能。我们设想将Braid作为分析的平台 基于图像的临床试验(IBCT)，其中我们目前有三个 分析。 我们的初步结果证明了高效自动化的必要性 针对大量对象的图像数据分割，对于强大的 对这些数据的统计分析，以及反映 在给定的IBCT中进行病理生理学研究。在IBCT中，我们是 分析，皮质和白质损害是 提出结构-功能假说。为此，我们建议 扩展Braid功能的三个具体目标：统计学的发展 脑部病变自动分割算法--贝叶斯算法的发展 基于多变量图谱的病变缺失分析方法，增强图谱 这将包括某些白质结构，除了皮质和 皮质下结构。这些扩展建立在Braid的优势之上 在第一阶段开发的形态分解图像表示法 这笔赠款。 我们将通过将我们的方法应用于数据集来测试这些对Braid的扩展 从儿童期额叶损伤的精神病理学研究(FLIC) 巴尔的摩老龄化纵向研究(BLSA)与心血管健康 研究(CHS)。BLSA和CHS是基于大规模流行病学图像的 临床试验，前者为为期9年的纵向研究，每年进行MR和 180名受试者的神经精神病学数据，后者是NHLBI赞助的项目 拥有超过3,600名参与者的广泛的人口统计、功能和MR数据。 FLIC研究正在收集脑部磁共振和广泛的神经精神病学数据 100例儿童创伤性脑损伤后。在分析这些数据和数据时， 与其他IBCT相比，Braid将增加我们对功能的理解 人脑的组织。

DESCRIPTION: (Applicant's Abstract) The overall goal of this project is the development of a digital brain image database (BRAID) that integrates image-processing and visualization capabilities, the statistical analysis of spatial and clinical data, and management of digital brain atlases, all accessible from a common user interface. The integration of these components is critical to BRAID's success in deriving clinically meaningful associations between the structure and function of the human brain. We envision BRAID as a platform for the analysis of image-based clinical trials (IBCT's), three of which we are currently analyzing. Our preliminary results demonstrate the need for efficient automated segmentation of image data for large numbers of subjects, for powerful statistical analysis of these data, and for atlases that reflect the pathophysiology being investigated in a given IBCT. In the IBCT's we are analyzing, cortical and white-matter lesions are central to the structure-function hypotheses being addressed. Toward these ends, we propose three specific aims to extend BRAID's functionality: development of statistical algorithms for automated segmentation of brain lesions, development of Bayesian methods for multivariate atlas-based lesion-deficit analysis, augmented atlas that will include certain white-matter structures in addition to cortical and subcortical structures. These extensions build on the strengths of BRAID's morphologically factored image representation developed in the first phase of this grant. We will test these extensions to BRAID by applying our methods to data sets from the Psychopathology of Frontal Lobe Injury in Childhood (FLIC) study, the Baltimore Longitudinal Study on Aging (BLSA), and the Cardiovascular Health Study (CHS). The BLSA and CHS are large-scale epidemiological image-based clinical trials, the former a 9-year longitudinal study with annual MR and neuropsychiatric data on 180 subjects, the latter an NHLBI sponsored project with extensive demographic, functional, and MR data on over 3,600 participants. The FLIC study is collecting brain MR and extensive neuropsychiatric data on 100 children after traumatic brain injury. In analyzing these data, and data from other IBCT's, BRAID will increase our understanding of the functional organization of the human brain.