Detection of brain metabolites in magnetic resonance spectroscopy
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2009
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| Online Access: | http://hdl.handle.net/1721.1/46602 |
| _version_ | 1811088102229278720 |
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| author | Kok, Trina |
| author2 | Elfar Adalsteinsson. |
| author_facet | Elfar Adalsteinsson. Kok, Trina |
| author_sort | Kok, Trina |
| collection | MIT |
| description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. |
| first_indexed | 2024-09-23T13:56:18Z |
| format | Thesis |
| id | mit-1721.1/46602 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T13:56:18Z |
| publishDate | 2009 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/466022019-04-10T17:59:33Z Detection of brain metabolites in magnetic resonance spectroscopy Kok, Trina Elfar Adalsteinsson. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. Includes bibliographical references (p. 59-61). While magnetic resonance imaging (MRI) derives its signal from protons in water, additional and potentially important biochemical compounds are detectable in vivo within the proton spectrum. The detection and mapping of these much weaker signals is known as magnetic resonance spectroscopy or spectroscopic imaging. Among the complicating factors for this modality applied for human clinical imaging are limited chemical-shift dispersion and J-coupling that cause spectral overlap and complicated spectral shapes that limit detection and separation of several brain metabolites using MR spectroscopic imaging. Existing techniques for improved detection include so-called 2D spectroscopy, where additional encoding steps aid in the separation of compounds with overlapping chemical shift. This is achieved by collecting spectral data over a range of timing parameters and introducing an additional frequency axis, fl. Spectral editing techniques attempt to enhance metabolite signal detection along fl in order to resolve specific metabolite signals. While these techniques have been shown to improve signal separation, they carry a penalty in scan time and more complicated reconstruction compared to conventional spectroscopy, and are often prohibitive when combined with spectroscopic imaging. The task of this thesis is to characterize and optimize existing 2D spectroscopy techniques for improved metabolite resolution with reduced number of timing steps through numerical simulation and experimental validation in phantoms. Trina Kok. S.M. 2009-08-26T17:01:16Z 2009-08-26T17:01:16Z 2008 2009 Thesis http://hdl.handle.net/1721.1/46602 426034896 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 61 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Kok, Trina Detection of brain metabolites in magnetic resonance spectroscopy |
| title | Detection of brain metabolites in magnetic resonance spectroscopy |
| title_full | Detection of brain metabolites in magnetic resonance spectroscopy |
| title_fullStr | Detection of brain metabolites in magnetic resonance spectroscopy |
| title_full_unstemmed | Detection of brain metabolites in magnetic resonance spectroscopy |
| title_short | Detection of brain metabolites in magnetic resonance spectroscopy |
| title_sort | detection of brain metabolites in magnetic resonance spectroscopy |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/46602 |
| work_keys_str_mv | AT koktrina detectionofbrainmetabolitesinmagneticresonancespectroscopy |