Research progress of artificial intelligence convolutional neural network in whole slide image analysis
- VernacularTitle:人工智能卷积神经网络在全视野数字切片图像分析中的应用进展
- Author:
ZHAO Mengmeng
1
;
WANG Yang
1
;
DENG Jiajun
1
;
SHE Yunlang
1
;
CHEN Chang
1
Author Information
1. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, 200433, P.R.China
- Publication Type:Journal Article
- Keywords:
Whole slide image;
artificial intelligence;
deep learning;
convolution neural network
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2019;26(11):1063-1068
- CountryChina
- Language:Chinese
-
Abstract:
Histopathology is still the golden standard for the diagnosis of clinical diseases. Whole slide image (WSI) can make up for the shortcomings of traditional glass slices, such as easy damage, difficult retrieval and poor diagnostic repeatability, but it also brings huge workload. Artificial intelligence (AI) assisted pathologist's WSI analysis can solve the problem of low efficiency and improve the consistency of diagnosis. Among them, the convolution neural network (CNN) algorithm is the most widely used. This article aims to review the reported application of CNN in WSI image analysis, summarizes the development trend of CNN in the field of pathology and makes a prospect.
