The purpose of this study was to synthesize Arterial Spin Labeling (ASL) cerebral blood flow (CBF) signal from blood-oxygen-level-dependent (BOLD) fMRI signal using deep machine learning (DL). Experimental results in the dual-echo Arterial Spin Labeling sequence show that the BOLD-to-ASL synthesize networks, the BOA-Net will yield similar cerebral blood flow value to that measured by ASL MRI and the cerebral blood flow maps produced by BOA-Net will show higher Signal-to-Noise Ratio (SNR) than that from ASL MRI.
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