摘要
胶囊内镜(CE)是检测小肠病变的主要手段,然而一次CE检查产生约6万张图像,筛选病变图像耗时、枯燥,且受医师经验和专业技术水平影响,易造成漏诊。因此,亟待研发能自动检测肠道病变的系统以解决上述问题。近年来,人工智能(AI)逐渐深入医学领域,以大数据和云计算为基础的计算机辅助诊断技术成为临床研究热点。以卷积神经网络(CNN)为代表的深度学习(DL)模型对病灶具有快速识别能力,可有效降低漏诊率。本文就AI技术在CE图像识别中的应用进展作一综述。
Capsule endoscopy(CE)is the main method to detect small intestinal lesions.However,a single CE examination produces about 60000 images,to screen lesion from the huge amount of images is a time-consuming,boring work,and is easy to cause missed diagnosis because of the limited experience and professional skill of physician.Therefore,it is urgent to develop a system that can automatically detect intestinal lesions.In recent years,the technique of artificial intelligence(AI)has gradually penetrated into the medical field,and the computer-aided diagnostic technology based on big data and cloud computing has become a hot spot of clinical research.The deep learning(DL)model represented by convolutional neural network(CNN)has the ability of rapid recognition of lesions and can effectively reduce the missed diagnosis rate.This article reviewed the application progress of AI technology in image recognition of CE.
作者
曹海燕
何松
CAO Haiyan;HE Song(Department of Gastroenterology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing (400010))
出处
《胃肠病学》
2020年第8期501-505,共5页
Chinese Journal of Gastroenterology
关键词
胶囊内镜
人工智能
深度学习
神经网络(计算机)
卷积神经网络
图像识别
Capsule Endoscopes
Artificial Intelligence
Deep Learning
Neural Networks(Computer)
Convolutional Neural Networks
Image Recognition
作者简介
通讯作者:何松,Email:hedoctor65@sina.com。
