医学信息2025，Vol.38Issue(18)：7-12,6.DOI:10.3969/j.issn.1006-1959.2025.18.002
基于卷积神经网络深度学习的病理图像自动诊断研究
Research on Automatic Diagnosis of Pathological Images Based on Convolutional Neural Network and Deep Learning
李春林 1周根鸿 1谭沁 1谢天逸1
作者信息
- 1. 武警湖南总队医院信息科,湖南 长沙 410006
- 折叠
摘要
Abstract
Pathological diagnosis is the"gold standard"for diseases such as tumors.However,traditional pathological diagnosis relies on the experience and professional knowledge of pathologists,which is time-consuming and prone to errors.With the development of computer vision and deep learning technologies,convolutional neural networks(CNNs)have made significant achievements in the field of image recognition.This article aims to explore the automatic diagnosis technology of pathological slices based on deep learning of convolutional neural networks.Through image recognition technology and convolutional algorithms,accurate automatic diagnosis of pathological slices can be achieved.The article first introduces the importance of pathological diagnosis and the current research status,and then elaborates on the basic principles of convolutional neural networks and their applications in automatic diagnosis of pathological slices,including key steps such as image preprocessing,feature extraction,and classification recognition.Finally,the article summarizes the current research hotspots and future development trends,providing new ideas and methods for automatic diagnosis of pathological sections.关键词
卷积神经网络/深度学习/病理图像/自动诊断Key words
Convolutional neural network/Deep learning/Pathological image/Automatic diagnosis分类
信息技术与安全科学引用本文复制引用
李春林,周根鸿,谭沁,谢天逸..基于卷积神经网络深度学习的病理图像自动诊断研究[J].医学信息,2025,38(18):7-12,6.
