The automatic detection of end diastole and end systole is the first step of any software developed for a fully automatic calculation of the ejection fraction. In this study, methods of image processing were applied to black and white echocardiographic image sequences corresponding to a cardiac cycle and the end systolic image number was automatically estimated. The first method took the advantage of the rapid mitral valve motion to estimate the end systole from the time signal intensity variation in a cavity region defined thanks to three landmarks usually used for the standard left ventricular segmentation. The second method was fully automatic; it was based on the left ventricular deformation during the cardiac cycle. The deformation curve was estimated using correlation and its minimal value was used to detect end systole. Method 3 was a combination of the two previous methods to overcome their limitations. The three methods were tested on a group of 37 patients (four chambers and two chambers apical views). The first image exhibiting the beginning of the mitral opening was considered as the end systolic on the visual readings. Compared with this visual reference reading, a linear regression led to a correlation coefficient r of 0.84 for the first method. This coefficient was improved to 0.87 for the second method and increased significantly to r=0.93 for the third method.