Cardiac volume/function assessment remains a critical step in daily cardiology and 3D ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation is, however, a challenging task due to the artifacts and low contrast-to-noise ratio of ultrasound imaging. In the present work, a fast and fully automatic framework for full cycle endocardial left ventricle segmentation is proposed. This approach couples the advantages of the B-spline explicit active surfaces framework, a purely image information approach, to those of statistical shape models to give prior information about the expected shape for an accurate segmentation. The segmentation is propagated throughout the heart cycle using a localized anatomical affine optical flow. It is shown that this approach not only outperforms other state-of-the-art methods in terms of distance metrics with mean average distances of 1.81±0.59 mm and 1.98±0.66 mm at end-diastole and end-systole respectively but is computationally efficient (in average 11 seconds per 4D image) and fully automatic.