Spatially Oriented Database for Digital Brain Images

数字脑图像空间定向数据库

• 批准号: 6929350
• 负责人: Edward H Herskovits
• 金额: $ 42.98万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-09-30 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6929350
• 关键词: aging; bioimaging /biomedical imaging; brain imaging /visualization /scanning; brain injury; brain morphology; computational neuroscience; computer data analysis; computer program /software; computer system design /evaluation; digital imaging; human data; image processing; information system analysis; information systems; longitudinal human study; magnetic resonance imaging; neuroanatomy; positron emission tomography; statistics /biometry; stroke

DESCRIPTION (provided by applicant): The overall goal of this project is the integration of advanced image-processing, data-analysis, and data management techniques into a brain-image database (BRAID), for the support of image-based clinical trials. The integration of these components has greatly aided our collaborators' management and analysis of image-based clinical trials (IBCTs) for the elucidation of structure-function associations for the human brain. In the previous cycle, we added segmentation capabilities, implemented Bayesian methods for lesion-deficit analysis, and began construction of a functional white-matter atlas based on lesion-deficit data. These methods, in conjunction with BRAID's visualization and other statistical tools, have resulted in contributions to the peer-reviewed clinical and engineering literature. However, our experience also demonstrates the need for extensions to BRAID. First, our segmentation algorithm is limited by its foundation on a statistical signal-intensity model of T 1-weighted spoiled gradient-recalled echo images. Second, given improvements in our registration techniques, we now have high-quality morphological data from our collaborators' IBCTs, but lack sophisticated methods for morphology-function analysis. Third, given the brain's plasticity, construction of an advanced functional atlas requires access to acute lesion-deficit data; our current collaborators are collecting subacute or chronic lesion-deficit data. Finally, we could facilitate the interchange of data, software, and analytic results with our collaborators and other colleagues by implementing BRAID based on open-source software. Towards these ends, we propose four specific aims to further extend BRAID's functionality: extension of our segmentation algorithm to incorporate more complex spatial and signal-intensity information; development of Bayesian methods for morphological analysis, to complement our Bayesian methods for lesion-deficit analysis; extension of BRAID to accommodate acute-stroke data, including magnetic-resonance (MR) perfusion and diffusion sequences; and reimplementation of BRAID using open-source components. We will test these image analysis, segmentation, and acutestroke extensions to BRAID using data from three IBCTs.

描述（由申请人提供）：该项目的总体目标是将先进的图像处理，数据分析和数据管理技术集成到脑图像数据库（BRAID）中，以支持基于图像的临床试验。这些组件的整合极大地帮助了我们的合作者管理和分析基于图像的临床试验（ibct），以阐明人类大脑的结构-功能关联。