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

Research progress of artificial intelligence convolutional neural network in whole slide image analysis

组织学病理是临床疾病诊断的金标准。全视野数字切片(whole slide image,WSI)的出现,虽弥补了传统的玻璃切片易损坏、检索困难以及诊断可重复性差的不足,但同时也带来了巨大的工作量。人工智能(artificial intelligence,AI)辅助病理医师的WSI分析,可解决工作效率低,提高诊断的一致性。其中,以深度学习卷积神经网络(convolution neural network,CNN)算法的应用最为广泛。本文综述目前已报道的CNN在WSI图像分析中的应用情况,总结CNN在病理学领域中的发展趋势并作出展望。

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.