Improved cardiac and vascular MRI using parallel imaging and compressed sensing

使用并行成像和压缩感知改进心脏和血管 MRI

• 批准号: 8197605
• 负责人: Mark Griswold
• 金额: $ 64.56万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-15 至 2014-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8197605
• 关键词: Address; Angiography; Area; Blood Vessels; Cardiac; Cardiovascular Diseases; Cardiovascular system; Clinical; Computer software; Computers; Computing Methodologies; Data; Diagnosis; Digital Subtraction Angiography; Evaluation; Evolution; Future; Generations; Goals; Gold; Health; Heart Diseases; Hour; Image; Imaging Techniques; Ionizing radiation; Kidney; Link; Magnetic Resonance Imaging; Measures; Medical Imaging; Methods; Metric; Morphologic artifacts; Noise; Patients; Performance; Perfusion; Process; Research Project Grants; Resolution; Role; Sampling; Scanning; Signal Transduction; Speed; Technology; Testing; Time; Vascular Diseases; Work; base; clinical Diagnosis; image reconstruction; imaging modality; improved; in vivo; innovation; novel; open source; reconstruction; simulation; theories; tomography; volunteer

DESCRIPTION (provided by applicant): The objective of this proposal is to produce a new level of gains in imaging speed and SNR for cardiac and vascular imaging by combining novel concepts of non-Cartesian parallel imaging techniques with the newly emerging compressed sampling theory. Compressed sensing promises to revolutionize the field of MRI by breaking the traditional link between imaging time and SNR. Here we will exploit these concepts to develop a set of completely new imaging strategies with dramatic increases in SNR and imaging speed. We specifically address computational limitations by developing an open source software distribution for high-end graphical processing units. These processors promise to dramatically reduce computational time across the board in medical imaging. Ultimately we believe that these technologies, when viewed as a whole, will result in a novel class of methods for cardiac and vascular diagnosis which will provide an increase in image quality, SNR and speed in MRI, perhaps unparalleled in the evolution of MRI, resulting in dramatically improved imaging of MR angiography, cardiac function and cardiac perfusion. Our specific aims are to: 1) develop and evaluate improved methods to acquire, and reconstruct multislice non-Cartesian parallel imaging methods for 2D MRI applications 2) develop and evaluate robust combined non-Cartesian parallel imaging and compressed sensing methods 3) develop and evaluate improved computational methods based on graphical processing units (GPUs) for the calculation of non-Cartesian parallel imaging, CG-HYPR and combined methods to achieve clinically acceptable reconstruction times and 4) validate parallel CG-HYPR methods for the evaluation of cardiovascular disease as a means to shorten total exam time and increase image quality.

描述（由申请人提供）：本提案的目的是通过将非笛卡尔并行成像技术的新概念与新出现的压缩采样理论相结合，将心脏和血管成像的成像速度和信噪比提高到新的水平。压缩传感有望打破成像时间和信噪比之间的传统联系，从而彻底改变 MRI 领域。在这里，我们将利用这些概念来开发一套全新的成像策略，显着提高信噪比和成像速度。我们通过为高端图形处理单元开发开源软件发行版来专门解决计算限制。这些处理器有望大幅减少医学成像领域的计算时间。最终，我们相信，从整体上看，这些技术将带来一类新型的心脏和血管诊断方法，提高 MRI 的图像质量、信噪比和速度，这在 MRI 的发展中可能是无与伦比的，从而显着改善 MR 血管造影、心脏功能和心脏灌注的成像。我们的具体目标是： 1) 开发和评估改进的方法来获取和重建用于 2D MRI 应用的多层非笛卡尔并行成像方法 2) 开发和评估稳健的组合非笛卡尔并行成像和压缩感知方法 3) 开发和评估基于图形处理单元 (GPU) 的改进计算方法，用于计算非笛卡尔并行成像、CG-HYPR 和 结合方法来实现临床可接受的重建时间，4) 验证并行 CG-HYPR 方法用于评估心血管疾病，作为缩短总检查时间和提高图像质量的手段。