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Abstract #0917

An automated deep neural network for denoising task-based fMRI data

Zhengshi Yang1, Xiaowei Zhuang1, Karthik Sreenivasan1, Virendra Mishra1, and Dietmar Cordes1,2

1Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States, 2University of Colorado, Boulder, CO, United States

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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