This paper introduces novel image-based methods for analyzing cardiorespiratory dynamics in ultrasound videos. The approach enables retrospective estimation of physiological phases, respiratory gating, and temporal superresolution, addressing challenges in preclinical cardiac studies. By transforming ultrasound videos into time series data and employing signal processing techniques, the methodology accurately captures cardiorespiratory motion. The results demonstrate the efficacy of the proposed methods for improved ultrasound analysis, providing valuable tools for cardiac research and evaluation.