The invention belongs to the technical field of image processing, and discloses an ultrasonic image left ventricular myocardium segmentation method and system and an application. The method comprisesthe steps of obtaining ultrasonic data, dividing the data into a training set, a verification set and a test set, and performing marking; enhancing the diversity of training set samples, interceptingan approximate left ventricular myocardium region, and performing histogram equalization and normalization operation on the data; using Pytorch to realize network segmentation, and storing a model having the best performance on the verification set; and measuring the thickness based on a segmentation result. According to the ultrasonic image left ventricular myocardium segmentation method based ona convolutional neural network, the left ventricular myocardium at the end of diastole can be automatically segmented, shape information of the left ventricular myocardium is added into the network to assist network learning, proposed mixed loss functions are optimized from three angles, and boundary information is further enhanced during learning; and the thickness can be automatically measuredbased on the segmentation result, and no post-processing is needed in the whole process.