摘要
人工智能领域不断创新发展,促使深度学习方法的理论和应用成为研究的热点。在医学领域中,传统的人工读片等医学图像分析方法已无法适应数量迅速增长的影像资料的诊断需求,因此,深度学习方法在医学图像中的应用备受关注。本文主要总结了深度学习方法在医学图像分割、图像分类识别和计算机辅助诊断方面的研究进展,最后进行了小结和展望。
With the development of artificial intelligence,the theory and application of deep learning method has become the focus study.In the field of medicine,medical image analysis methods such as reading images by human eyes are gradually unable to meet the diagnostic needs of an increasing amount of images.Therefore,the application of deep learning methods in medical images is a hotspot.This paper summarizes the research progress of deep learning methods in medical image segmentation,image classification and recognition,and computer aided diagnosis.
作者
艾飞玲
马圆
田思佳
王肖楠
张凤
郭秀花
AI Felling;MA Yuan;TIAN Sijia;WANC Xiaonan;ZHANG Feng;CUO Xiuhua(School of Public Health,Capital Medical University,Beijing 100069)
出处
《北京生物医学工程》
2018年第4期433-438,共6页
Beijing Biomedical Engineering
基金
国家自然科学基金(81773542)资助
关键词
深度学习
医学图像
图像分割
图像分类和识别
计算机辅助诊断
deep learning
medical image
image segmentation
image recognition and classification
computer aided diagnosis
