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极其重要的能力。功能成像研究中的标准化、生长、衰老和疾病中形状变化的研究、在术中图像上叠加手术计划以及几何畸变校正是图像配准的重要应用的例子。两个科内都有几十个注册需求 以及学科间应用。因此，图像配准性能的任何改进都将对科学和临床界产生直接影响。尽管图像重建算法取得了许多进步，但使用多种模态（或组织对比度）进行图像配准实际上是一个尚未开发的领域。占主导地位的框架是将主体的单个图像配准到目标的另一个单个图像，并且如果主体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、评估和验证一种解释非常简单但相当激进的多模式注册想法。 基本思想是从与目标图像具有相同组织对比度和强度范围的主体图像合成“代理”图像，然后使用平方和差之类的传统度量来进行主体之间的配准代理和目标。初步结果表明这种方法有显着的好处。在资助中，我们将：1）通过探索其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的三个关键应用，以验证该方法并制定最佳实践原则； 3）编写开源软件，利用“代理”图像概念进行图像合成、相似性计算以及刚性和可变形配准。用于用户最喜欢的图像注册方法的合成图像的软件以及以优化方式执行整个“代理”注册过程的软件都将作为开源计算机代码公开提供。这项研究的结果将改变研究人员和从业者获取和使用神经科学研究和临床医学数据的方式，从而开创图像配准的新时代。

项目成果

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

基于超级体素的随机森林合成框架，用于双向 MR/CT 合成。

• 发表时间: 2017
• 作者: Zhao, Can;Carass, Aaron;Lee, Junghoon;Jog, Amod;Prince, Jerry L
• 通讯作者: Prince, Jerry L

Effects of Spatial Resolution on Image Registration.

空间分辨率对图像配准的影响。

• 发表时间: 2016-02-27
• 作者: Zhao, Can;Carass, Aaron;Jog, Amod;Prince, Jerry L
• 通讯作者: Prince, Jerry L

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning.

基于传统 MRI 的基于多图谱的 CT 合成，以及基于 MRI 的放射治疗计划的基于补丁的细化。

• 发表时间: 2017-02
• 作者: Lee, Junghoon;Carass, Aaron;Jog, Amod;Zhao, Can;Prince, Jerry L
• 通讯作者: Prince, Jerry L

Simulation and Synthesis in Medical Imaging.

医学成像中的模拟与合成。

• 发表时间: 2018-03
• 影响因子: 10.6
• 作者: Frangi, Alejandro F;Tsaftaris, Sotirios A;Prince, Jerry L
• 通讯作者: Prince, Jerry L

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。

• 发表时间: 2017-02
• 作者: Dewey, Blake E;Carass, Aaron;Blitz, Ari M;Prince, Jerry L
• 通讯作者: Prince, Jerry L