Interoperability and Usability Enhancement to DTI ToolKit
Interoperability and Usability Enhancement to DTI ToolKit
批准号:
7624778
负责人:
JAMES C GEE
金额:
$15.75万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-04-01 至 2012-03-31
关键词:
AddressAdoptedAdoptionAlgorithmsAnatomyArchitectureAreaArtsAtlasesAwarenessBrainBrain DiseasesCaringCatalogingCatalogsClassificationClinicalClinical ResearchComplementComputer softwareCountryDataData AnalysesDiffusionDiffusion Magnetic Resonance ImagingDiseaseDocumentationDrug FormulationsEnvironmentFeedbackFiberGoalsHealthImageImage AnalysisImaging DeviceInformaticsInstitutionInstructionMagnetic Resonance ImagingMeasurementMeasuresMethodsMetricMicroscopicNatureOutputPatientsPlayPopulationProceduresProcessPropertyProtocols documentationResearch InfrastructureResearch PersonnelResourcesRoleSensitivity and SpecificityShapesSoftware ToolsStudy SubjectTissuesUnited States National Institutes of HealthVariantbasecostdesignfile formatgraphical user interfaceimage reconstructionimage registrationimaging modalityimprovedin vivointerestinteroperabilityneuroimagingnovelpublic health relevanceresearch studytoolusabilitywater diffusionwhite matterwhite matter change
中文摘要
描述(由申请人提供):弥散张量成像(DTI)在协助临床和生物医学研究人员检查和识别可能导致各种脑部疾病的白质变化方面发挥着越来越重要的作用。为了定位和量化这些变化,通常要进行基于全脑体素的分析,这需要一个空间归一化步骤,将研究对象的共享解剖结构置于空间对齐中。目前可用的神经成像分析软件中的归一化方法没有针对DTI数据的特殊张量特性进行优化,因此,不能充分利用这些测量中编码的信息来更准确地对齐脑白质束。DTI-TK是一个多平台软件工具包,专门用于解决这一限制。它由一套工具组成,这些工具实现了特定于DTI数据的图像处理算法,其中关键是一个最先进的可变形图像配准工具,该工具在转换公式中通过显式张量重定向优化了全张量相似性度量。总之,该工具包为DTI数据提供了最先进的、公开可用的空间规范化软件。在临床研究中,DTI-TK已被证明可以提高空间归一化的质量,增强统计推断的能力。它可以在网上免费获得,并为来自全国各地机构的越来越多的调查人员提供支持。本提案的目标是通过改进DTI-TK的互操作性、可用性和文档,使DTI-TK能够被更广泛的神经成像研究人员使用。互操作性增强包括对NIfTI图像格式的全面支持,特别强调对NIfTI标头中编码的图像空间和患者空间之间转换的正确解释,以及对其他流行的DTI工具的兼容性支持。提出的可用性增强包括实现MATLAB工具箱,以支持SPM5工作流中DTI-TK空间规范化例程的集成。建议对文档进行改进,包括对所有工具的详细使用说明进行系统编目,以及将DTI-TK与其他神经成像工具相结合的常见使用场景的面向任务的教程。为了增加其可访问性,DTI-TK将利用NIH神经成像信息学工具和资源交换中心(NITRC)进行传播。这项工作将帮助更多的用户使用该工具,并创建一个用户和开发人员可以高效交互的环境,从而对互操作性和可用性进行额外的高影响增强。公共卫生相关性:拟议的项目旨在改善DTI- tk的互操作性、可用性和文档化,DTI- tk是一个软件工具包,旨在支持和改进使用扩散张量成像(DTI)获得的数据分析,DTI是一种新的磁共振成像方式,为健康和疾病中的脑白质的体内成像研究开辟了道路。具体来说,该工具包将使研究人员能够访问最先进的DTI注册和规范化功能,包括构建特定人群的模板,这将显著提高白质变化群体研究的敏感性和特异性。这将使本项目对每一个新用户的影响倍增,并对科学产出的质量和意义产生广泛的影响。
英文摘要
DESCRIPTION (provided by applicant): Diffusion tensor imaging (DTI) is playing an increasingly important role in assisting clinical and biomedical investigators examine and identify white matter changes that may underly various brain disorders. To localize and quantify such changes, whole brain voxel-based analysis is typically performed, which requires a spatial normalization step that serves to place the shared anatomy of study subjects into spatial alignment. The normalization methods in currently available software for neuroimaging analysis are not optimized for the specialized tensorial nature of DTI data, and, consequently, do not take full advantage of the information encoded in these measurements for more accurate alignment of brain white matter tracts. DTI-TK is a multiplatform software toolkit that has been specifically developed to address this limitation. It consists of a suite of tools that implement image manipulation algorithms specific for DTI data, key among which is a state- of-the-art deformable image registration tool that optimizes full-tensor similarity metrics with explicit tensor reorientation in the transformation formulation. Together, the toolkit provides the most advanced, publicly available spatial normalization software specific for DTI data. DTI-TK has been demonstrated to improve the quality of spatial normalization and enhance the power of statistical inference in clinical studies. It is freely available online and supports a growing number of investigators from institutions across the country. The objective of this proposal is to make DTI-TK accessible to a much wider audience of neuroimaging researchers by making improvements to its interoperability, usability and documentation. Interoperability enhancements include comprehensive support for the NIfTI image format, with a special emphasis on correct interpretation of the transformations between image space and patient space encoded in NIfTI headers, and compatibility support for other popular DTI tools. Proposed usability enhancement includes the implementation of a MATLAB toolbox to support the integration of the DTI-TK spatial normalization routine within SPM5 workflows. Proposed improvements to documentation involve both systematic cataloging of detailed usage instructions for all of the tools and task-oriented tutorials for common usage scenarios that combine DTI-TK with other neuroimaging tools. Toward increasing its accessibility, DTI-TK will leverage the NIH Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) for dissemination. This effort will help expose many more users to the tool and create an environment in which users and developers can interact productively, leading to additional high- impact enhancements to interoperability and usability. PUBLIC HEALTH RELEVANCE: The proposed project aims to improve the interoperability, usability and documentation of DTI-TK, a software toolkit designed to support and improve the analysis of data acquired using diffusion tensor imaging (DTI), a novel magnetic resonance imaging modality that has opened the way to in vivo imaging studies of brain white matter in health and disease. Specifically, the toolkit will give researchers access to state-of-the-art DTI registration and normalization functionality, including the construction of population-specific templates, that will significantly enhance the sensitivity and specificity of group studies of white matter changes. This will multiply the effect of this project with each new user and have a wide influence on the quality and significance of scientific output.
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