Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks

To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edited magnetic resonance spectroscopy (MRS) data. An ablation s...

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Veröffentlicht in:	Magnetic resonance imaging 2024-09, Vol.111, p.186-195
Hauptverfasser:	Bugler, Hanna, Berto, Rodrigo, Souza, Roberto, Harris, Ashley D.
Format:	Artikel
Sprache:	eng
Schlagworte:	1H spectroscopy Algorithms Brain - diagnostic imaging Brain - metabolism Choline - metabolism Computer Simulation Convolutional neural networks (CNN) Deep Learning Frequency and phase correction GABA-edited MRS gamma-Aminobutyric Acid - analysis gamma-Aminobutyric Acid - metabolism Humans Machine learning Magnetic Resonance Spectroscopy - methods Neural Networks, Computer Pre-processing Signal-To-Noise Ratio
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