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Abstract #2688

1D Convolutional Neural Network for Estimating BOLD Signal from Oscillating Steady State Signal

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) for fMRI commonly combines images across a fast oscillation to produce a steady time series suitable for fMRI analysis. The signal magnitude derived from L2-norm combination can be sensitive to frequency variations, which can exacerbate physiological noise, particularly respiration. Here, we use a 1D convolutional neural network (1DCNN) to directly estimate the underlying T2* BOLD response from both simulated and real OSSI fMRI signals. We demonstrated that our technique reduces B0 fluctuations and thermal noise as compared to the L2-norm combined OSSI fMRI signal.

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