Measuring left ventricle (LV) volume is a challenging problem in physiological study. One of the non-intrusive methods that is possible for this task is echocardiography. By extracting left ventricle area from ultrasound images, the volume can be approximated by the size of the left ventricle area. The core of the problem becomes the identification of the left ventricle in noisy images considering spatial temporal information. We propose adaptive sparse smoothing for left ventricle segmentation for each frame in echocardiography video for the benefit of robustness against strong speckle noise in ultrasound imagery. Then we adjust the identified left ventricle areas (as curves in polar coordinate system) further by a fixed rank principal component analysis as post processing. This method is tested on two data sets with labelled left ventricle areas for some frames by expert physiologist and compared against active contour based method. The experimental results show clearly that the proposed method has better accuracy than that of the competitor.