Recent progress in optical coherence tomography (OCT) allows imaging dynamic structures and fluid flow within scattering tissue, such as the beating heart and blood flow in mouse embryos. Accurate representation and analysis of these dynamic behaviors require reducing the noise of the acquired data. Although noise can be reduced by averaging multiple neighboring pixels in space or time, such operations reduce the effective spatial or temporal resolution that can be achieved. We have developed a computational postprocessing technique to restore image sequences of cyclically moving structures that preserves frame rate and spatial resolution. The signal-to-noise ratio (SNR) is improved by combining images from multiple cycles that have been synchronized with a temporally elastic registration procedure. Here we show how this technique can be applied to OCT images of the circulatory system in cultured mouse embryos. Our technique significantly improves the SNR while preserving temporal and spatial resolution.