The presented approach utilizes artificial neural networks trained on magnetic field monitoring data in order to predict respiration induced B0-field fluctuations in the brain under the condition of normal breathing. From the predicted B0-field fluctuations it is possible to distinguish the respiration induced resonance offset from the resonance offsets induced by other sources during the course of the experiment. This allows for the quantification of breathing related B0-field fluctuations in the brain of normally breathing healthy volunteers. Furthermore it was observed that the B0-field fluctuations resulting from normal respiration show individual spatial dynamics for every volunteer.
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