Minimum Redundancy Spatiotemporal MRI

0201876 Bresler自70年代初问世以来，磁共振成像（MRI）已成为首选的诊断成像工具。虽然其早期应用主要限于静止物体，但近年来，MRI也被证明对于动态成像应用非常有用，例如心脏、功能或介入成像。 动态磁共振成像（D-MRI）面临的一个重要挑战是获得高的空间和高的时间分辨率。在过去的二十年中，已经开发了许多快速成像方法，包括快速扫描技术、用于并行采集的相控阵RF线圈以及数据空间的减少采样。尽管在快速MRI方面取得了这些进展，但许多应用仍然严重依赖于额外的加速，几乎所有应用都可以从中受益。例子包括3D多相心脏成像，冠状动脉造影和斑块表征，心脏成像没有屏气，弥散张量功能脑成像，和介入MRI与高组织对比度和时间resolution.General目标提出的研究是开发，实施和测试一个新的统一的理论框架，最小冗余D-MRI数据采集和图像重建。在这个框架中，动态成像被视为一个高维图像重建问题，与时间是一个独立的轴。在MRI序列设计、数据采集和图像重建的步骤中明确考虑采集期间的时间变化，而不是试图通过足够快的采集来冻结所有运动。该方法将借鉴和扩展PI在过去几年中引入的理论和算法，这些理论和算法为成像过程的显着加速提供了潜力。此外，本项目中开发的理论和技术与快速扫描方法和基于相控阵RF线圈的方法相结合，将产生比任何一种单独方法更大的组合加速。

0201876BreslerSince its inception in the early 70's, magnetic resonance imaging (MRI) has become a premier diagnostic imaging tool. Although its early applications were largely limited to stationary objects, MRI has also proven extremely useful, in recent years, for dynamic imaging applications, such as cardiac, functional or interventional imaging. An important challenge confronting dynamic MRI (D-MRI) is obtaining both high spatial and high temporal resolutions. Over the last two decades, many fast imaging methods including fast-scan techniques, phased array RF coils for parallel acquisition, and reduced sampling of the data space have been developed. In spite of these advances in fast MRI, many applications are still critically dependent on additional speedups, and virtually all applications could benefit from them. Examples include 3D multiphase cardiac imaging, coronary angiography and plaque characterization, cardiac imaging without breath-holding, diffusion-tensor functional brain imaging, and interventional MRI with high tissue contrast and temporal resolution.The general goal of the proposed research is to develop, implement and test a new unified theoretical framework for minimum-redundancy D-MRI data acquisition and image reconstruction. In this framework, dynamic imaging is treated as a higher-dimensional image reconstruction problem, with time being an independent axis. Instead of attempting to freeze all motion by sufficiently fast acquisition, time variation during acquisition is explicitly accounted for in the steps of MRI sequence design, data acquisition, and image reconstruction. The approach will draw on and extend theories and algorithms introduced by the PIs over the past few years, which offer the potential for significant speedups of the imaging process. Furthermore, combination of the theory and techniques developed in this project with fast scan methods and with methods based on phased-array RF coils will produce combined speedups, greater than any one of the individual approaches.