An example of improving the SNR of arterial spin-labeling MR imaging using deep learning. An example of improving the SNR of arterial spin-labeling MR imaging using deep learning. The model is trained using low-SNR ASL images acquired with only a single repetition, while the reference image is a high-SNR ASL image acquired with multiple repetitions (in this case, 6 repetitions). Proton-density-weighted images (acquired routinely as part of the ASL scans for quantitation) and T2-weighted images are also used as inputs to the model to improve performance. The results of passing the low-SNR ASL image through the model are shown on the right, a synthetic image with improved SNR. In this example, the root-mean-squared error (RSME) between the reference image and the synthetic image compared with the original image is reduced nearly 3-fold, from 29.3% to 10.8%. G. Zaharchuk et al. AJNR Am J Neuroradiol 2018;39:1776-1784 ©2018 by American Society of Neuroradiology