To improve the efficiency of measuring left ventricular ejection fraction（LVEF）based on echocardiography, This paper proposes a new method for automatically calculating LVEF based on deep learning. Firstly, The convolution neural network (CNN), trained verified and tested by 38,153 marked echocardiography data, is used to divide the collected echocardiographic data into five categories and apical four-chamber view(A4C) and apical two-chamber view(A2C) are obtained. Then, the fully convolutional networks (FCN) ,using VGG-19 as the backbone architecture, trained and verified by collected 3871 A2C and 4679 A4C data, is used for segmenting the left ventricle of the two obtained views and the LVEF is obtained. Finally, The test result shows that the accuracy of obtaining the A4C and A2C is 96.8% and the true positive rate of segmentation is over 88.8%. A error is 0.038947 between the automatic and manual. The proposed method is calculated by the machine, which is more accurate and efficient than the conventional method.