Spectral Representation of Neurochemicals With Phase, Frequency Offset, and Lineshape Invariance: Application to JPRESS for In Vivo Concentration and T2 Mapping by Deep Learning. | Synapse
Spectral Representation of Neurochemicals With Phase, Frequency Offset, and Lineshape Invariance: Application to JPRESS for In Vivo Concentration and T2 Mapping by Deep Learning.
The research aims to investigate the application of deep learning in quantifying neurochemical concentrations and T2 mapping.
Utilized deep learning algorithms for quantifying neural metabolites.
Applied JPRESS techniques for spectral analysis.
Focused on the invariance of phase, frequency offset, and lineshape in data processing.
Demonstrated effective quantification of metabolite concentrations.
Achieved reliable T2 mapping results.
Showed high practical viability for the proposed method in real-time applications.
Abstract
This study demonstrates that deep learning can be used for automatically quantifying both metabolite concentrations and transverse relaxation times with high practical viability.