Improving FLAIR SAR efficiency at 7T by adaptive tailoring of adiabatic pulse power through deep learning B1+ estimation

Purpose The purpose of this study is to demonstrate a method for specific absorption rate (SAR) reduction for 2D T2‐FLAIR MRI sequences at 7 T by predicting the required adiabatic radiofrequency (RF) pulse power and scaling the RF amplitude in a slice‐wise fashion. Methods We used a time‐resampled f...

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Veröffentlicht in:	Magnetic resonance in medicine 2021-05, Vol.85 (5), p.2462-2476
Hauptverfasser:	Abbasi‐Rad, Shahrokh, O’Brien, Kieran, Kelly, Samuel, Vegh, Viktor, Rodell, Anders, Tesiram, Yasvir, Jin, Jin, Barth, Markus, Bollmann, Steffen
Format:	Artikel
Sprache:	eng
Schlagworte:	Adiabatic Adiabatic flow Amplitudes Artificial neural networks B1+ profile convolutional neural network (CNN) Deep learning Delay time FLAIR Homogeneity Image quality Inhomogeneity Inversion Magnetic resonance imaging Mathematical analysis Neural networks Radio frequency Reduction SA2RAGE Scaling specific absorption rate (SAR) TR‐FOCI
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