NIREP: Non-rigid Image Registration Evaluation Project

NIREP：非刚性图像配准评估项目

• 批准号: 7429698
• 负责人: GARY E CHRISTENSEN
• 金额: $ 29.31万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7429698
• 关键词: Algorithms; Anatomy; Atlases; Benchmarking; Brain; Communities; Complex; Computer software; Computers; Computing Methodologies; Data; Databases; Evaluation; Feedback; Goals; Gold; Grant; Human; Image; Individual; Link; Linux; Magnetic Resonance Imaging; Maps; Methods; Metric; Modality; Mono-S; Numbers; Performance; Personal Computers; Phase; Population; Research; Simulate; Standards of Weights and Measures; Testing; Validation; Variant; computer program; image registration; innovation; performance tests; programs; prototype; software development; tool

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.

描述（由申请人提供）： 非刚性图像配准（NIR）是在存在个体内和个体间解剖变异的情况下进行形态学比较的重要工具。人们已经开发了许多近红外方法，但由于逐点图像间的对应关系通常是未知的，因此特别难以评估。我们建议开发和测试一个框架，全面的近红外方法评估，不需要一个“黄金标准”或地面真理对应图。非刚性图像配准评估项目（NIREP）将开发软件工具，并提供共享的图像验证数据库，用于非刚性图像配准算法的严格测试。NIREP将通过使用大量图像群体、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估标准的数量和类型来开发评估标准和指标，从而扩大先前验证项目的范围。 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非刚性图像配准算法的性能评估指标。此外，这些标准将被纳入一个可导出的计算机程序，以自动评估非刚性图像配准算法的配准精度。 本项目的R21具体目标是：（1）构建一个注释丰富的人脑MR图像数据库，以评估和基准单模态非刚性图像配准性能。(2)开发非刚性图像配准性能指标，建立小变形非刚性配准基准。(3)开发一个可导出的Linux可执行程序，以在高性能个人计算机上评估2D和3D非刚性配准性能。 本项目的R33具体目标是：（1）扩展非刚性配准评价的共享参考数据库。(2)建立大变形配准基准和增加评估指标的框架。(3)向研究界传播NIREP软件和附加说明的参考数据库。(4)使用NIREP软件测试ITK和SPM中包含的主要非刚性图像配准算法的性能。