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

这个子项目是众多研究子项目之一

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. 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.