摘要
近年来,随着医学影像数据规模不断扩大,医学图像进入大数据时代。在海量数据驱动下,人工智能理论及应用逐渐走向成熟,促使深度学习算法成为研究热点。在医学领域中,传统的人工阅片诊断方式已无法满足迅速增长医学影像的诊断需求,因此,基于深度学习的自动化医学影像分析备受关注。文章主要对深度学习算法在医学图像分割、分类识别、计算机辅助诊断方面的研究进展予以综述。
In recent years,as the scale of medical imaging data continues to expand,medical images have entered the era of big data.Driven by massive data,artificial intelligence theories and applications are gradually maturing,making deep learning algorithms a research hotspot.In the medical field,the traditional manual diagnostic methods for reading films have been unable to meet the rapidly growing diagnostic needs of medical imaging.Therefore,automated medical image analysis based on deep learning has attracted much attention.This article reviews the research progress of deep learning algorithms in medical image segmentation,classification and recognition,and computer-aided diagnosis.
作者
吴扬
WU Yang(North China University of Water Resources and Electric Power,Zhengzhou 450045,China)
出处
《电脑知识与技术》
2020年第19期174-176,共3页
Computer Knowledge and Technology
关键词
深度学习
医学图像分割
医学图像分类识别
计算机辅助诊断
deep learning
medical image segmentation
medical image classification and recognition
computer-aided diagnosis
