| 摘要: |
| 医工结合是未来医学发展的趋势，人工智能与大数据的融合将为影像医学翻开崭新的一页。心肌增强超声（myocardial contrast echocardiography , MCE）的临床应用目前处于定性诊断阶段，现有研究表明心肌灌注定量分析优于定性分析，但由于目前的后处理软件操作繁琐，耗时明显，且严重依赖操作者经验水平，其重复性和准确性较差，导致心肌灌注定量分析无法广泛应用于临床。部分研究将人工智能应用于心肌轮廓描记，以自动/半自动方式获取感兴趣区（region of interest, ROI），为心肌灌注定量分析的广泛应用提供可能，本综述旨在回顾人工智能在心肌增强超声心肌轮廓描记的应用研究现状及发展趋势。 |
| 关键词: 人工智能，深度学习，超声心动图，心肌增强超声，增强超声 |
| DOI： |
| 投稿时间：2019-09-17修订日期：2019-10-09 |
| 基金项目: |
|
| Application Status and Development Trend of Artificial Intelligence in Myocardial Contrast Echocardiography |
| limingqi,feihongwen |
| (Guangdong Provincial People‘s Hospital, Guangdong Academy of Medical Sciences) |
| Abstract: |
| 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. |
| Key words: artificial intelligence, deep learning, echocardiography, myocardial contrast echocardiography, enhanced ultrasound |
