深度学习技术在医学影像分析中的应用与展望  

Application and Prospect of Deep Learning Technology in Medical Image Analysis

作　　者：刘立兵 傅励瑶 LIU Li-bing;FU Li-yao(Chongqing Communication Design Institute Co.,Ltd,Chongqing 400041,China)

机构地区：[1]重庆市信息通信咨询设计院有限公司,重庆400041

出　　处：《新一代信息技术》2024年第1期24-28,共5页New Generation of Information Technology

摘　　要：深度学习在医学影像分割、配准和融合等方面取得了显著成功,应用实例包括计算机辅助诊断、个性化治疗和临床决策支持等。深度学习技术在医学影像分析中展现出巨大的潜力,极大地提升了医疗诊断的准确性和效率。本文讨论了深度学习在医学影像处理领域的主要技术发展及其应用,重点介绍了基于深度学习的分割、配准、融合和联邦学习方法在增强诊断准确性和辅助治疗中的关键作用。最后,本文探讨了当前技术的局限性以及未来的发展方向,旨在为医学影像处理领域的研究和应用提供有价值的参考。Deep learning technology has shown great potential in medical image analysis,greatly improving the accuracy and efficiency of medical diagnosis.This paper discusses the major technological developments and applications of deep learning in the field of medical image processing,with a focus on the key roles of deep learning based segmentation,registration,fusion,and federated learning methods in enhancing diagnostic accuracy and assisting treatment.Finally,this article explores the limitations of current technology and future development directions,aiming to provide valuable references for research and application in the field of medical image processing.

关 键 词：深度学习 图像分析 医学影像分析 分析技术应用 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]