{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/147548"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/147548","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Iyer, Siddharth Srinivasan"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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