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Abstract #2352

Estimating B0 changes in Oscillating Steady State Imaging (OSSI)  using an Artificial Neural Network

Mariama Salifu1, Melissa Haskell2, and Douglas C Noll1
1Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 2Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States


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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