NIREP: Non-rigid Image Registration Evaluation Project

描述(由申请人提供)： 非刚性图像配准(NIR)是在存在内部和个体间解剖差异的情况下进行形态比较的重要工具。已经开发了许多近红外方法，但由于逐点图像间对应通常是未知的，因此尤其难以评估。我们建议开发和测试一个不需要“黄金标准”或地面真实对应图的综合近红外方法评估框架。非刚性图像配准评估项目(NIREP)将开发软件工具并提供共享图像验证数据库，以严格测试非刚性图像配准算法。NIREP将扩大先前验证项目的范围，方法是使用大量图像群体制定评价标准和指标，使用注释丰富的图像数据库，使用计算机模拟数据，以及增加评价标准的数量和类型。 这个项目的目标是建立、维护和认可一套标准化的相关基准和度量标准，用于非刚性图像配准算法的性能评估。此外，这些标准将被合并到一个可输出的计算机程序中，以自动评估非刚性图像配准算法的配准精度。 R21项目的具体目标是：(1)构建一个标注丰富的人脑MR图像库，以评估和基准单模非刚性图像配准性能。(2)制定非刚性图像配准性能指标，建立小变形非刚性配准基准。(3)开发了一个可导出的Linux可执行程序，用于在高性能个人计算机上评估2D和3D非刚性配准的性能。 本项目R33的具体目标是：(1)扩展可共享的参考数据库，用于非刚性注册评估。(2)建立大变形登记基准和增加评价指标的框架。(3)向研究界传播NIREP软件和带注释的参考数据库。(4)利用NIREP软件对ITK和SPM中包含的主要非刚体图像配准算法进行了性能测试。

DESCRIPTION (provided by applicant): Non-rigid image registration (NIR) is an essential tool for morphologic comparisons in the presence of intra and inter-individual anatomic variations. Many NIR methods have been developed, but are especially difficult to evaluate since point-wise inter-image correspondence is usually unknown. We propose to develop and test a framework for comprehensive NIR method evaluation that does not require a "Gold Standard" or ground truth correspondence map. The Non-rigid Image Registration Evaluation Project (NIREP) will develop software tools and provide shared image validation databases for rigorous testing of non-rigid image registration algorithms. NIREP will extend the scope of prior validation projects by developing evaluation criteria and metrics using large image populations, using richly annotated image databases, using computer simulated data, and increasing the number and types of evaluation criteria. The goal of this project is to establish, maintain, and endorse a standardized set of relevant benchmarks and metrics for performance evaluation of non-rigid image registration algorithms. Furthermore, these standards will be incorporated into an exportable computer program to automatically evaluate the registration accuracy of non-rigid image registration algorithms. The R21 Specific Aims of this project are to: (1) Construct a richly annotated human brain MR image database to evaluate and benchmark mono-modality non-rigid image registration performance. (2) Develop non-rigid image registration performance metrics and establish small deformation non-rigid registration benchmarks. (3) Develop an exportable Linux executable program to evaluate 2D and 3D non-rigid registration performance on a high-performance personal computer. The R33 Specific Aims of this project are to: (1) Expand the shareable reference database for non-rigid registration evaluation. (2) Establish large deformation registration benchmarks and a framework for adding evaluation metrics. (3) Disseminate NIREP software and annotated reference databases to the research community. (4) Test performance of major non-rigid image registration algorithms contained in ITK and SPM using the NIREP software.