摘要
目的围绕在乳腺癌筛查与诊断中开展的基于神经网络的人工智能的研究,对其现状及临床应用价值进行概述。方法检索中国知网和Pub Med数据库中神经网络和人工智能在乳腺X线、乳腺超声、乳腺磁共振及乳腺病理学诊断方面的联合研究,进行综述。结果乳腺X光数字乳腺图像数据库(DDSM)等乳腺X线公共数据库为神经网络在乳腺X线领域的研究提供了原材料,国内外运用神经网络对乳腺疾病影像进行筛查及诊断的研究中,以乳腺X线开展得最多。神经网络在乳腺X线及乳腺彩超领域均可做到病灶分割、测量、特征分析、良恶性判断及出具结构化报告。神经网络在乳腺超声领域的应用集中在乳腺疾病良恶性的诊治。三星麦迪逊集团率先将研究成果嫁接在超声仪器中。乳腺MRI具有较多高通量信息,率先成为人工神经网络与影像组学联合研究的切入点。病理图像拥有较多需测量的数据信息,数据量化分析是神经网络的优势,二者结合,可显著提高病理医生的诊断时效。结论研究人工智能在乳腺癌的筛查与诊断中的应用,实质是分析神经网络在乳腺影像及病理领域的应用。目前人工智能筛查可以作为医师辅助工具,是一个客观诊断参考助手,用于提高乳腺超声的诊断时效。随着医学影像组学及神经网络彼此的发展,人工智能在医学领域的应用可扩展到手术方式设计、疗效评估、预后分析等。
Objective To study the application of artificial intelligence based on neural network in breast cancer screening and diagnosis, and to summarize its current situation and clinical application value. Method The combined studies of neural network and artificial intelligence in the directions of breast mammography, breast ultrasound, breast magnetic resonance, and breast pathology diagnosis in CNKI and PubMed database were reviewed. Results Public databases of mammography, such as Digital Database for Screening Mammography (DDSM), provided raw materials for the research of neural network in the field of mammography. Mammography was the most widely used data for screening and diagnosis of breast diseases by neural network. In the field of mammography and color doppler ultrasound, neural network could segment, measure, and analyze the characteristics, judge the benign or malignant, and issue a structured report. The application of neural network in the field of breast ultrasound focused on the diagnosis and treatment of benign and malignant breast diseases. Samsung Madison Group taken the lead in grafting research results into ultrasound instruments. Breast MRI had a lot of high-throughput information, which had became the breakthrough point for the joint study of artificial neural network and imaging omics. Pathological images had more data information to be measured, and quantitative analysis of data was the advantage of neural network. The combination of the two kinds of methods could significantly improve the diagnosis time of pathologists. Conclusions To study the application of artificial intelligence in breast cancer screening and diagnosis is to analyze the application of neural network in breast imaging and pathology. At present, artificial intelligence screening can be used as a physician assistant and an objective diagnostic reference assistant, to improve the diagnosis of breast disease. With the development of medical image histology and neural network, the application of artificial intelligence in medica
作者
陈瑶
吕青
CHEN YAO;Lü Qing(Department of Breast Surgery,West China Hospital,Sichuan University,Chengdu,610041,P. R. China)
出处
《中国普外基础与临床杂志》
CAS
2019年第5期625-630,共6页
Chinese Journal of Bases and Clinics In General Surgery
关键词
乳腺癌
人工智能
神经网络
深度学习
综述
breast cancer
artificial intelligence
neural network
deep learning
review
