The combination of medicine and engineering is the trend of medical development, and the integration of artificial intelligence and big data will turn a new page for imaging medicine. At present, the clinical application of myocardial contrast echocardiography(MCE) is in the stage of qualitative diagnosis. The existing research shows that the quantitative analysis of myocardial perfusion is better than qualitative analysis, but the current post-processing software is tedious, time-consuming, and relies heavily on the level of experience of the operator. As a consequence, its repeatability and accuracy are poor, resulting in the quantitative analysis of myocardial perfusion can not be widely used in the clinic. In some studies, artificial intelligence was applied to myocardial profilometry, and the automatic/semi-automatic acquisition of region of interest(ROI) provided the possibility for the wide application of myocardial perfusion quantitative analysis. This review aims to summarize the application and trend of artificial intelligence on myocardial profilometry of MCE.