A semi-automated method for analyzing cardiac quiescence of anatomical cardiac features from two-dimensional echocardiographic cine data is presented. The method utilizes both active contour and optical flow techniques for feature identification and tracking. A curvature-based potential surface was used in the active contour calculations to attract the contour to regions of inflection on the image surface rather than the standard gradient-based surface that attracts the contour to strong edges. After identifying the feature in each frame, the frame-to-frame correlation matrix of the feature was calculated with correlation values corresponding to how well the feature matched between frames. Therefore prolonged regions of high correlation correspond to periods of cardiac quiescence. The location and duration of these periods were automatically identified from the correlation matrix by finding the largest region around each time index with a mean correlation above a specified threshold. In parallel, the position of the feature was calculated for each frame by finding the centroid of the pixel locations inside the contour. From this trajectory, the magnitude of the two-dimensional velocity was calculated. These methods were used to analyze the quiescence of the interventricular septum from an apical four-chamber echocardiogram performed on a human subject. Correlation-derived quiescent phases were observed to coincide with periods of the cardiac cycle with minimal velocity magnitude.