IMAGE RECONSTRUCTION FROM SPARSELY SAMPLED (K, T)-SPACE DATA

稀疏采样（K，T）空间数据的图像重建

• 批准号: 8362776
• 负责人: ZHI-PEI LIANG
• 金额: $ 8.29万
• 依托单位: NORTHERN CALIFORNIA INSTITUTE/RES/EDU
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8362776
• 关键词: Algorithms; Development; Drug Formulations; Funding; Grant; Image; Joints; Magnetic Resonance Imaging; Methodology; Modeling; National Center for Research Resources; Neurodegenerative Disorders; Perfusion; Phase; Principal Investigator; Research; Research Infrastructure; Resources; Sampling; Series; Source; Time; United States National Institutes of Health; Validation; cost; data space; image reconstruction; imaging modality; novel; spatiotemporal

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Aim 1: Optimizing a novel (k, t)-space formulation of the generalized series model to allow joint spatiotemporal modeling of the time-varying object function encountered in various spatiotemporal imaging applications of the proposed imaging center (e.g., dynamic perfusion imaging). Aim 2: Development of an efficient image reconstruction algorithm that can handle both conventional and sensitivity-encoded (k, t)-space data collected using a single or multiple phased array coils. Aim 3: Validation of the proposed (k, t)-space imaging method using the methodologies described in the Validation section.

该副本是利用资源的众多研究子项目之一 由NIH/NCRR资助的中心赠款提供。对该子弹的主要支持 而且，副投影的主要研究员可能是其他来源提供的 包括其他NIH来源。 列出的总费用可能 代表subproject使用的中心基础架构的估计量， NCRR赠款不直接向子弹或副本人员提供的直接资金。 AIM 1：优化广义串联模型的新颖（K，T）空间公式，以允许在所提出的成像中心的各种时空成像应用中遇到的时变对象函数的联合时空建模（例如，动态灌注成像）。 AIM 2：开发有效的图像重建算法，该算法可以处理使用单个或多个阶段阵列线圈收集的常规和灵敏度编码（K，T）空间数据。 AIM 3：使用验证部分中描述的方法对所提出的（K，T）空间成像方法进行验证。