Undersampling in Magnetic Resonance Metabolic Imaging Using Prior Anatomical Knowledge
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Date
2020
Publication Type
Conference Paper
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yes
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Abstract
Studying the metabolic pathways is important as insufficient energy supply to the cardiac muscle has a major role in heart failure. Dysfunctional substrate metabolism eventually leads to an impaired contractile function typical for heart failure. For assessing cardiac metabolism health, hyperpolarized magnetic resonance spectroscopy is used herein, for imaging pyruvate, lactate and bicarbonate metabolites. Due to the inherently short lifetime of the hyperpolarized signal, the use techniques to acquire dynamic images in a short amount of time are necessary. To this end, we use Cartesian undersampling techniques in conjunction with a spectral localization algorithm (SLIM) based on prior anatomical knowledge. Successful image reconstructions were obtained using undersampling factors of up to three, with minor degradation in image quality in simulations (11.8%) and preliminary in-vivo case (24.6%). © 2020 IEEE.
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published
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Book title
2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
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Volume
Pages / Article No.
9160701
Publisher
IEEE
Event
20th International Conference on Environment and Electrical Engineering (EEEIC 2020) and 4th Industrial and Commercial Power System Europe (I&CPS 2020) (virtual)
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Subject
Magnetic-resonance spectroscopy; Metabolic imaging; Compartment based regularization; Medical imaging
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Notes
Due to the Corona virus (COVID-19) the conference was conducted virtually.