On Improving the Acquisition and Reconstruction Of Spatio-Temporal Magnetic Resonance Imaging

Abstract

Magnetic Resonance Imaging (MRI) is a non-invasive but slow imaging modality that provides unparalleled flexibility in acquiring multiple forms of soft-tissue contrast. Recently, there has been a lot of interest in mapping the inherent magnetization properties of the underlying human tissue and in temporally resolving the acquired data. Broadly classified as spatio-temporal MRI, these methods yield unprecedented details of the human anatomy and function, improving clinical diagnostic performance and prognosis. However, such methods are inherently high-dimensional, resulting in encoding-intensive data acquisition processes and computationally-intensive reconstructions. This begets long acquisition and reconstruction times, making such methods difficult to integrate into clinical workflows. This thesis aims to improve the acquisition and reconstruction times of spatio-temporal MRI to enable its use in clinical and neuroscientific setting.