The Online Brain Atlas Reconciliation Tool

在线脑图谱协调工具

基本信息

批准号：
8298256
负责人：
PARTHA Pratim MITRA
金额：
$ 40.66万
依托单位：
COLD SPRING HARBOR LABORATORY
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-08-01 至 2014-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8298256
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

项目摘要

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）：目前在神经影像社区（以及神经科学中的其他地方），研究人员采用了各种递延程序和地图集来对其工作感兴趣的大脑区域。结果是，许多不同的标签用于指示相同的空间区域，在某些情况下，使用相同的标签来指示不同的区域。这个众所周知的命名法问题是对跨研究尤其是杂种的负面影响，以前通过在同义和/或层次与层次相关的区域标签之间开发语义映射来解决。但是，通过这种语义映射的区域绘制的区域所描述的区域之间的空间关系可能非常复杂，理解不足，并且没有充分捕获。我们已经基于分析各种脑部分析之间的空间关系开发了一种新的地图集一致性问题的方法。通过将我们的指标应用于现在正在使用的不同分割方案，我们发现分区之间的总体一致性相当贫穷，这表明需要“ \ meta-atlas”或系统的程序来绘制新的图谱之间的映射。通过此授予建议，我们希望为这些目的而开发的工具和努力，使他们能够使用NEURS的努力，并将其努力延伸到NEUR，并使其努力保持努力，并使其保持努力。通过自定义的网站在线上的比较和元分析工具，是针对算法的创新，以增强对大脑的一致性分析和命名。从分析地图集中使用的大脑区域标签到Birnlex本体论，Birn Atlas互操作性框架中的其他Web服务，以及为Birn网格上的神经图像处理管道添加适当的功能。成功完成我们的项目将增强神经影像学数据集的数据整合和荟萃分析，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本和临床神经科学，但是存在一些显着的挑战 - 特别是，多种大脑图书馆和命名法方案，可以进行跨研究和元分析。我们已经开发了一个框架来处理这个地图集的一致性问题，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的神经影像社区，扩展和改善初步分析，并将与Birn和Cabig基础设施集成。