Oscillating steady state imaging (OSSI) is a novel fMRI acquisition method which produces a high SNR T2*-weighted signal. Physiological and drift induced B0 changes cause undesired signal distortions which can significantly diminish functional contrast in OSSI fMRI. Here, we investigated a method of rapidly estimating quantitative B0 field changes from OSSI images using an artificial neural network (ANN) model. Our results demonstrated that this technique can be used to rapidly measure field changes, which has the potential to be used for prospective and retrospective B0 field correction in OSSI.
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