In this paper, we develop a novel method based on dynamic mode decomposition (DMD) to extract resting-state networks from short windows of noisy, high-dimensional fMRI data, allowing RSNs from single scans to be resolved robustly at a temporal resolution of seconds. This automated DMD-based method is a powerful tool to characterize spatial and temporal structures of RSNs in individual subjects.