心血管图像的深度学习方法

Yankun Cao, Zhi Liu, Pengfei Zhang, Yushuo Zheng, Yongsheng Song, Li-zhen Cui
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引用次数: 23

摘要

在医学领域,医学图像的分析和处理在疾病诊断中起着重要的辅助作用。近年来,越来越多的研究者开始关注医学图像处理中的模式识别、分类和分割等处理技术。心血管疾病是目前危害人类健康的主要疾病之一。通过深入学习,对心血管疾病的诊断和治疗具有重要意义。为了使深度学习更好地应用于心血管疾病,本文首先概述了心血管疾病的发展和成因,然后介绍了深度学习的几种理论模型,然后结合现有技术总结了深度学习在心脏图像分割、分类等方面的应用。最后,对未来的发展方向进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning Methods for Cardiovascular Image
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.
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