Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a widely used non-invasive imaging technology for both clinical diagnosis and neuroscientific research. However, the imaging sensitivity and specificity of brain MRI are limited by the well-known technical challenge of MRI acquisition—low image encoding efficiency...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Published: |
Massachusetts Institute of Technology
2022
|
| Online Access: | https://hdl.handle.net/1721.1/138978 https://orcid.org/0000-0001-8975-2775 |
| _version_ | 1811072475520303104 |
|---|---|
| author | Wang, Fuyixue |
| author2 | Setsompop, Kawin |
| author_facet | Setsompop, Kawin Wang, Fuyixue |
| author_sort | Wang, Fuyixue |
| collection | MIT |
| description | Magnetic resonance imaging (MRI) is a widely used non-invasive imaging technology for both clinical diagnosis and neuroscientific research. However, the imaging sensitivity and specificity of brain MRI are limited by the well-known technical challenge of MRI acquisition—low image encoding efficiency, leading to limited acquisition speed, spatial resolution and signal-to-noise ratio especially for in-vivo imaging. In order to address these challenges, this thesis presents newly developed spatiotemporal encoding methods, which are used to improve the sensitivity and specificity as well as provide time and cost savings for different MRI applications, including diffusion, quantitative relaxometry and functional imaging. The novel encoding strategies in high-dimensional space together with efficient data sampling schemes allow better use of radio-frequency pulse, modern receiver coil arrays and shared data correlation. The high imaging efficiency provided by these spatiotemporal acquisition methods was demonstrated to help overcome several long-standing challenges in brain MRI, which should help increase its diagnosis power and gain further understanding of the structural and functional organization of the human brain. |
| first_indexed | 2024-09-23T09:06:33Z |
| format | Thesis |
| id | mit-1721.1/138978 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T09:06:33Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1389782022-01-15T04:01:42Z Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging Wang, Fuyixue Setsompop, Kawin Harvard-MIT Program in Health Sciences and Technology Magnetic resonance imaging (MRI) is a widely used non-invasive imaging technology for both clinical diagnosis and neuroscientific research. However, the imaging sensitivity and specificity of brain MRI are limited by the well-known technical challenge of MRI acquisition—low image encoding efficiency, leading to limited acquisition speed, spatial resolution and signal-to-noise ratio especially for in-vivo imaging. In order to address these challenges, this thesis presents newly developed spatiotemporal encoding methods, which are used to improve the sensitivity and specificity as well as provide time and cost savings for different MRI applications, including diffusion, quantitative relaxometry and functional imaging. The novel encoding strategies in high-dimensional space together with efficient data sampling schemes allow better use of radio-frequency pulse, modern receiver coil arrays and shared data correlation. The high imaging efficiency provided by these spatiotemporal acquisition methods was demonstrated to help overcome several long-standing challenges in brain MRI, which should help increase its diagnosis power and gain further understanding of the structural and functional organization of the human brain. Ph.D. 2022-01-14T14:42:22Z 2022-01-14T14:42:22Z 2021-06 2021-06-15T14:03:02.334Z Thesis https://hdl.handle.net/1721.1/138978 https://orcid.org/0000-0001-8975-2775 In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Wang, Fuyixue Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging |
| title | Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging |
| title_full | Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging |
| title_fullStr | Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging |
| title_full_unstemmed | Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging |
| title_short | Spatiotemporal Encoding Methods for Brain Magnetic Resonance Imaging |
| title_sort | spatiotemporal encoding methods for brain magnetic resonance imaging |
| url | https://hdl.handle.net/1721.1/138978 https://orcid.org/0000-0001-8975-2775 |
| work_keys_str_mv | AT wangfuyixue spatiotemporalencodingmethodsforbrainmagneticresonanceimaging |