Multimodal image registration by proxy image synthesis

通过代理图像合成进行多模态图像配准

• 批准号: 8919113
• 负责人: Jerry L Prince
• 金额: $ 34.18万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8919113
• 关键词: Adopted; Affect; Aging; Algorithms; Appearance; Area; Atlases; Clinical; Clinical Medicine; Communities; Computer Vision Systems; Computer software; Data; Data Collection; Databases; Development; Diffusion Magnetic Resonance Imaging; Disease; Environment; Evaluation; Functional Imaging; Functional Magnetic Resonance Imaging; Geometry; Goals; Grant; Growth; Health; Image; Java; Lead; Liquid substance; Magnetic Resonance Imaging; Manufacturer Name; Measures; Medical Imaging; Medical Research; Methods; Modality; Modeling; Motion; Multimodal Imaging; Neurosciences; Operative Surgical Procedures; Pathology; Performance; Physiologic pulse; Plague; Population; Positron-Emission Tomography; Predisposition; Procedures; Process; Proxy; Radial; Research; Research Personnel; Resources; Scanning; Science; Shapes; Specific qualifier value; Sum; Surface; Testing; Therapeutic; Tissues; Validation; Variant; Weight; Work; Writing; X-Ray Computed Tomography; base; clinical Diagnosis; computer code; cone-beam computed tomography; image reconstruction; image registration; imaging software; improved; intraoperative imaging; longitudinal analysis; neuroimaging; novel strategies; open source; outcome forecast; public health relevance; shape analysis; statistics; success; targeted imaging; theories; tool; vector; web site

DESCRIPTION (provided by applicant): Image registration is a fundamentally important capability in modern neuroscience and clinical medicine. Normalization in functional imaging studies, studies of shape changes in growth, aging, and disease, overlaying surgical plans on intraoperative images, and geometric distortion correction are examples of important applications of image registration. There are dozens of needs for registration in both intrasubject and intersubject applications as well. Therefore, any improvement in image registration performance will have an immediate impact on the scientific and clinical communities. Despite numerous advances in image reconstruction algorithms, the use of multiple modalities (or tissue contrasts) to carry out image registration is a virtually untapped area. The vastly dominant framework is to register a single image of the subject to another single image of the target, and if multiple images are available of either subject or target, they are registered by using the transformation derived from the single image registration. The proposed research will develop, evaluate, and validate a very simply explained but quite radical idea for multi-modal registration. The basic idea is to synthesize a "proxy" image from the subject image that has the same tissue contrast and intensity range as the target image and then use a conventional metric such as sum-of-square difference to carry out the registration between the subject proxy and target. Preliminary results demonstrate significant benefits in this approach. In the grant we will: 1) Optimize "proxy" multimodal image registration by exploring its theoretical justification as well a key parameters of the overall approach; 2) Apply "proxy" multimodal image registration to three key applications in neuroscience in order to validate the method and develop principles of best practice; and 3) Write open source software to carry out image synthesis, similarity computation, and rigid and deformable registration using the "proxy" image concept. Both the software to synthesize images for use in a user's favorite image registration method as well as software to carry out the entire "proxy" registration process in an optimized way will be made publicly available as open source computer code. The results of this research will lead to a new era in image registration by changing the way researchers and practitioners acquire and use data for neuroscientific studies and clinical medicine.

描述（由申请人提供）：图像配准是现代神经科学和临床医学中一项至关重要的能力。功能成像研究中的标准化、生长、衰老和疾病中的形状变化研究、术中图像上的手术计划叠加以及几何失真校正是图像配准的重要应用的示例。在两个学科内都有几十个注册需求 和跨学科应用。因此，图像配准性能的任何改进都将对科学和临床社区产生直接影响。尽管在图像重建算法方面取得了许多进展，但使用多种模态（或组织对比度）来进行图像配准实际上是一个尚未开发的领域。最主要的框架是将受试者的单个图像配准到目标的另一个单个图像，并且如果受试者或目标的多个图像可用，则通过使用从单个图像配准导出的变换来配准它们。拟议的研究将开发，评估和验证一个非常简单的解释，但相当激进的想法多模式注册。 其基本思想是从具有与目标图像相同的组织对比度和强度范围的受试者图像合成“代理”图像，然后使用诸如平方和差的常规度量来执行受试者代理和目标之间的配准。初步结果表明，在这种方法中的显着好处。在赠款中，我们将：1）通过探索“代理”多模态图像配准的理论依据以及整体方法的关键参数来优化“代理”多模态图像配准：2）将“代理”多模态图像配准应用于神经科学中的三个关键应用，以验证该方法并发展最佳实践原则;以及3）编写开放源代码软件以使用“代理”图像概念来执行图像合成、相似性计算以及刚性和可变形配准。用于用户喜爱的图像登记方法的合成图像软件以及以优化方式执行整个“代理”登记过程的软件都将作为开放源码计算机代码公开提供。这项研究的结果将通过改变研究人员和从业人员获取和使用神经科学研究和临床医学数据的方式，引领图像配准的新时代。

项目成果

Tree-Encoded Conditional Random Fields for Image Synthesis.

• DOI: 10.1007/978-3-319-19992-4_58
• 发表时间: 2015
• 期刊: Information processing in medical imaging : proceedings of the ... conference
• 作者: Jog A;Carass A;Pham DL;Prince JL
• 通讯作者: Prince JL

Efficient Multi-Atlas Registration using an Intermediate Template Image.

使用中间模板图像进行高效的多图集配准。

• DOI: 10.1117/12.2256147
• 发表时间: 2017
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Dewey,BlakeE;Carass,Aaron;Blitz,AriM;Prince,JerryL
• 通讯作者: Prince,JerryL

A supervoxel based random forest synthesis framework for bidirectional MR/CT synthesis.

• DOI: 10.1007/978-3-319-68127-6_4
• 发表时间: 2017-09
• 期刊: Simulation and synthesis in medical imaging : ... International Workshop, SASHIMI ..., held in conjunction with MICCAI ..., proceedings. SASHIMI (Workshop)
• 作者: Zhao C;Carass A;Lee J;Jog A;Prince JL
• 通讯作者: Prince JL

Effects of Spatial Resolution on Image Registration.

空间分辨率对图像配准的影响。

• DOI: 10.1117/12.2217322
• 发表时间: 2016
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Zhao,Can;Carass,Aaron;Jog,Amod;Prince,JerryL
• 通讯作者: Prince,JerryL

Self Super-resolution for Magnetic Resonance Images.

• DOI: 10.1007/978-3-319-46726-9_64
• 发表时间: 2016-10
• 期刊: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
• 作者: Jog A;Carass A;Prince JL
• 通讯作者: Prince JL