The Online Brain Atlas Reconciliation Tool

在线脑图谱协调工具

• 批准号: 8115087
• 负责人: PARTHA Pratim MITRA
• 金额: $ 37.66万
• 依托单位: COLD SPRING HARBOR LABORATORY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2013-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8115087
• 关键词: Address; Agreement; Algorithms; Applications Grants; Area; Atlases; Attention; Basic Science; Brain; Brain imaging; Brain region; Brain scan; Clinical; Clinical Research; Communities; Complex; Computer software; Custom; Data; Data Set; Development; Disease; Ensure; Environment; Extensible Markup Language; Housing; Human; Image; Imaging Techniques; Internet; Label; Link; Magnetic Resonance Imaging; Maps; Masks; Measures; Meta-Analysis; Methodology; Methods; Metric; Mus; Network-based; Neurology; Neurosciences; Nomenclature; Ontology; Procedures; Process; Property; Protocols documentation; Research; Research Design; Research Infrastructure; Research Personnel; Resources; Rest; Scheme; Semantics; Services; Slice; Software Tools; Surface; Techniques; Testing; Translating; Tweens; Work; acronyms; base; cancer Biomedical Informatics Grid; data exchange; data integration; design; improved; innovation; interest; interoperability; neuroimaging; neuropsychiatry; novel; novel strategies; programs; prototype; public health relevance; repository; spatial relationship; tool; usability; web services; web site

DESCRIPTION (provided by applicant): Currently in the neuroimaging community (and elsewhere in neuroscience), researchers employ a variety of deferent procedures and atlases to parcellate and label brain regions that are of interest in their work. The result is that many dierent labels are used to indicate the same spatial region, and in some cases, the same label is used to indicate dierent regions. This well-known nomenclature problem, which has the negative consequence of making cross-study comparison especially dicult, has previously been addressed by developing semantic mappings between synonymous and/or hierarchically-related region labels. How- ever, the spatial relationships between regions as delineated by dierent atlases can be quite complex, are poorly understood, and are not adequately captured by such semantic mappings. We have developed a new approach to this atlas concordance problem based on analyzing the spatial relationships between various brain parcellations. By applying our metrics to dierent parcellation schemes now in use, we found that the overall concordance between partitions is rather poor, which suggests the need for a \meta-atlas" or systematic procedures for mapping between dierent atlases. Through this grant proposal, we wish to expand upon the tools and methods which we have developed for this purpose, and make them available to the neuroscience community. The rest specic aim will be to make the atlas comparison and meta-analysis tools available online through an interactive, customizable website. The second aim is for algorithmic innovations to enhance the concordance analysis of brain parcellations and nomenclatures. This will include the incorporation of additional atlases and functionality as well as further theoretical developments of overall atlas concordance measures. The third aim is integration with BIRN and caBIG infrastructures. This will include mappings from the brain region labels used in the analyzed atlases to the BIRNLex ontology, additional web services within the BIRN Atlas Interoperability Framework, and adding appropriate functionality to the neuroimage processing pipelines on the BIRN GRID. Successful completion of our project will enhance data integration and meta-analysis of neuroimaging data sets, and broadly impact both basic and clinical research in neurology and neuropsychiatry. PUBLIC HEALTH RELEVANCE: Functional brain imaging techniques have revolutionized basic and clinical neuroscience, but there are some signicant challenges - particularly, a multiplicity of brain atlases and nomenclature schemes that make cross-study comparison and meta analysis dicult. We have developed a framework to deal with this atlas concordance problem, including quantitative measures and software tools. The proposed research will make these tools available to the general neuroimaging community, expand and improve the preliminary analysis and will integrate with the BIRN and caBIG infrastructures.

描述（由申请人提供）：目前在神经成像领域（以及神经科学的其他领域），研究人员采用各种不同的程序和地图集来包裹和标记他们工作中感兴趣的大脑区域。结果是许多不同的标签被用于指示相同的空间区域，并且在某些情况下，相同的标签被用于指示不同的区域。这个著名的命名问题，这有负面影响，使跨研究比较，特别是dicult，以前已经解决了开发同义和/或层次相关的区域标签之间的语义映射。然而，由不同地图集描绘的区域之间的空间关系可能相当复杂，理解不多，并且不能被这样的语义映射充分捕获。 我们已经开发了一种新的方法，这个地图集一致性问题的基础上分析各种大脑包裹体之间的空间关系。通过将我们的指标应用于现在使用的dierent parcellation方案，我们发现分区之间的整体一致性相当差，这表明需要一个“元地图集”或系统的程序来映射dierent地图集。通过这项拨款提案，我们希望扩大我们为此目的开发的工具和方法，并将其提供给神经科学界。 其余的具体目标将是通过一个互动的、可定制的网站使地图集比较和荟萃分析工具在线可用。第二个目标是算法创新，以加强大脑包裹和命名的一致性分析。这将包括纳入更多的地图集和功能，以及进一步从理论上发展地图集统一的总体措施。第三个目标是与BIRN和caBIG基础设施集成。这将包括从分析地图集中使用的大脑区域标签到BIRNLex本体的映射，BIRN Atlas互操作性框架内的其他Web服务，以及向BIRN GRID上的神经图像处理管道添加适当的功能。我们项目的成功完成将增强神经影像数据集的数据集成和荟萃分析，并广泛影响神经病学和神经精神病学的基础和临床研究。 公共卫生相关性：功能性脑成像技术已经彻底改变了基础和临床神经科学，但也存在一些重大挑战-特别是，脑图谱和命名方案的多样性，使交叉研究比较和Meta分析变得困难。我们已经制定了一个框架来处理这个地图集一致性问题，包括定量措施和软件工具。拟议的研究将使这些工具可用于一般神经影像学社区，扩展和改进初步分析，并将与BIRN和caBIG基础设施集成。