Deep Learning Methods for Cardiovascular Image

Abstract

In the medical field, the analysis and processing of medical images plays an important auxiliary role in the diagnosis of diseases. In recent years, more and more researchers have begun to pay attention to such processing technologies as pattern recognition, classification and segmentation in medical image processing. Cardiovascular disease is one of the most important diseases that endanger human health at present. It is very meaningful to diagnose and treat cardiovascular disease by means of in-depth learning. In order to make deep learning better applied to cardiovascular diseases, this paper first outlines the development and causes of cardiovascular diseases, then describes several theoretical models of deep learning, and then summarizes the application of deep learning in heart image segmentation, classification and other aspects combined with existing technologies. Finally, the future direction of development is prospected.