dc.contributor.advisor | Esmaeili, Morteza | |
dc.contributor.author | Gencher, Johan Levent | |
dc.date.accessioned | 2023-08-02T15:51:22Z | |
dc.date.available | 2023-08-02T15:51:22Z | |
dc.date.issued | 2023 | |
dc.identifier | no.uis:inspera:135002646:69194800 | |
dc.identifier.uri | https://hdl.handle.net/11250/3082359 | |
dc.description.abstract | Magnetic resonance (MR) spectroscopy (MRS) modalities provide non-invasive
and non-ionization in vivo imaging tools for preclinical and clinical examinations.
Brain examinations’ standard clinical MR protocols comprise several anatomical
imaging techniques. This work describes the principal physics behind clinical
MRS, spectral analysis paradigm, and MRS applications in clinical routines. The
excellent contrast from the brain’s anatomy partly relies on water’s hydrogen nuclei
relaxation time differences in tissues. Peak fitting and a linear combination of
simulated metabolites are standard algorithms to estimate metabolite intensities
from MR spectra. This thesis aims to implement two popular algorithms on in vivo
clinical MR spectra and compare the quantification estimations of two methods. | |
dc.description.abstract | Magnetic resonance (MR) spectroscopy (MRS) modalities provide non-invasive
and non-ionization in vivo imaging tools for preclinical and clinical examinations.
Brain examinations’ standard clinical MR protocols comprise several anatomical
imaging techniques. This work describes the principal physics behind clinical
MRS, spectral analysis paradigm, and MRS applications in clinical routines. The
excellent contrast from the brain’s anatomy partly relies on water’s hydrogen nuclei
relaxation time differences in tissues. Peak fitting and a linear combination of
simulated metabolites are standard algorithms to estimate metabolite intensities
from MR spectra. This thesis aims to implement two popular algorithms on in vivo
clinical MR spectra and compare the quantification estimations of two methods. | |
dc.language | eng | |
dc.publisher | uis | |
dc.title | Analyzing Magnetic Resonance Spectroscopy Data | |
dc.type | Bachelor thesis | |