Minimum Redundancy Spatiotemporal MRI

最小冗余时空 MRI

• 批准号: 0201876
• 负责人: Yoram Bresler
• 金额: $ 29.7万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0201876&HistoricalAwards=false
• 关键词: Minimum; Redundancy; Spatiotemporal; MRI

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.

自20世纪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。尽管其早期应用主要局限于静止物体，但近年来，MRI在动态成像应用（如心脏、功能或介入成像）方面也被证明非常有用。动态磁共振成像（D-MRI）面临的一个重要挑战是获得高空间和高时间分辨率。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射频线圈以及减少数据空间采样。尽管快速MRI取得了这些进步，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。例如，3D多相心脏成像、冠状动脉造影和斑块表征、无屏气的心脏成像、弥散张量功能脑成像以及具有高组织对比度和时间分辨率的介入性MRI。本研究的总体目标是开发、实施和测试一个新的统一理论框架，用于最小冗余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，时间是一个独立的轴。不是试图通过足够快的采集来冻结所有运动，而是在MRI序列设计、数据采集和图像重建的步骤中明确考虑了采集过程中的时间变化。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，该项目中开发的理论和技术与快速扫描方法和基于相控阵射频线圈的方法相结合，将产生比任何一种单独方法更大的组合速度。