基于深度学习的计算机辅助诊断系统在肺癌早期诊断中的应用与进展  

Application and development of computer-aided diagnosis systems based on deep learning for the early diagnosis of lung cancer

作　　者：刘婧[1] 张莺[1] Liu Jing;Zhang Ying(Department of Nuclear Medicine,the Second Affiliated Hospital of Zhejiang University School of Medicine,Hangzhou 310009,China)

机构地区：[1]浙江大学医学院附属第二医院核医学科,杭州310009

出　　处：《国际放射医学核医学杂志》2020年第1期22-26,共5页International Journal of Radiation Medicine and Nuclear Medicine

基　　金：国家重点研发计划项目(2016YFA0100900、2016YFA0100902);国家自然科学基金(81501508)。

摘　　要：胸部CT扫描是肺癌早期筛查和诊断的主要检查手段,应用于胸部影像诊断领域的基于深度学习的计算机辅助诊断(CAD)系统可对CT图像上的肺结节进行检测和分类。深度学习技术可提高CAD系统的性能,尤其是在提高肺结节检测的准确率和降低假阳性率方面。笔者就CAD系统中的深度学习模型在肺结节中的应用现状和研究进展作一综述。Chest CT scan is the primary medical imaging method performed for the early screening and diagnosis of lung cancer.Deep-learning based computer aided diagnosis(CAD)system for chest CT imaging is helpful for detecting and classifying pulmonary nodules.Deep-learning techniques can improve the performance of CAD systems,especially in enhancing the accuracy of pulmonary nodule detection and reducing false-positive rates.This article reviewed the current application status of deep-learning models in CAD systems and the progress that has been achieved in using these systems for imaging pulmonary nodules.

关 键 词：人工智能 肺肿瘤 诊断 计算机辅助 神经网络(计算机) 深度学习 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术] R734[医药卫生—肿瘤]