Deep neural networks (DNN) recently have gained increasing interest in neuroimaging research for different applications. However, it remains to be an open question whether and how artificial neural networks can be used for denoising neuroimaging data. In this study, we have designed a DNN network for denoising task-based fMRI data. The result showed that DNN can efficiently reduce physiological fluctuation and achieve more homogeneous fMRI activation maps.
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