Multimodal image registration by proxy image synthesis

项目摘要/摘要(最多30行文本) 图像配准是现代神经科学和临床的一项重要功能。 医药。功能成像研究中的归一化，生长、衰老和 疾病，在术中图像上覆盖手术计划，以及几何失真矫正 图像配准的重要应用实例。有几十种注册需求 主题内和主题间的应用程序也是如此。因此，形象的任何改善 注册绩效将对科学界和临床界产生直接影响。 尽管图像重建算法取得了许多进展，但使用多种模式(或 组织对比度)进行图像配准实际上是一个未开发的领域。占主导地位的 框架是将对象的单个图像配准到目标的另一个单个图像，并且如果 对象或目标的多个图像可用，它们是通过使用 由单幅图像配准得到的变换。拟议的研究将会发展， 评估和验证一个非常简单的解释但相当激进的多模式注册的想法。这个 基本思想是从具有相同组织对比度的被摄体图像中合成一幅“代理”图像 和强度范围作为目标图像，然后使用诸如平方和的传统度量 在主体代理和目标之间进行登记的差异。初步结果 在这种方法中显示出显著的好处。在赠款中，我们将：1)优化“代理”多式联运 通过探讨图像配准的理论依据以及关键参数的整体 方法；2)将“代理”多模式图像配准应用于神经科学中的三个关键应用 以验证该方法并制定最佳实践原则；以及3)编写开放源码 执行图像合成、相似度计算以及刚性和可变形配准的软件 使用“代理”形象的概念。这两款软件都可以合成用户最喜欢的图像 图像配准方法以及在图像配准过程中执行整个代理注册过程的软件 优化的方式将以开源计算机代码的形式公开提供。这样做的结果 研究将通过改变研究人员和研究人员的方式来引领图像配准的新纪元 从业者获取和使用数据用于神经科学研究和临床医学。

Project Summary/Abstract (Max 30 lines of text) 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 as 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.