摘要
肺结核的影像学形态往往呈多样性,因此,如何鉴别诊断肺结核一直以来是常规影像学研究的重点与难点。近年来,深度学习在辅助影像诊断方面有了飞快发展。深度学习擅长识别大量图像数据中的复杂模式,可大大提高医师的诊断准确性及工作效率。笔者将对深度学习在影像诊断及肺结核影像诊断中的应用、不足及展望进行综述。
The imaging morphology of pulmonary tuberculosis is often diversified,therefore,how to differentiate the diagnosis of pulmonary tuberculosis has always been the focus and difficulty of conventional imaging studies.In recent years,deep learning has made rapid development in assisted image diagnosis.Deep learning is good at identifying complex patterns in a large amount of image data,which can greatly improve the diagnostic accuracy and work efficiency of doctors.This paper reviews the application,deficiency and prospect of deep learning in pulmonary tuberculosis and imaging diagnosis.
作者
吴键
侯代伦
WU Jian;HOU Dai-lun(Imaging Department,Beijing Chest Hospital,Capital Medical University,Beijing 101149,China;Department of Function,Shaanxi Provincial Tuberculosis Control Institute/The Fifth People’s Hospital of Shaanxi Province,Xi’an 710100,China)
出处
《中国防痨杂志》
CAS
CSCD
2022年第1期91-94,共4页
Chinese Journal of Antituberculosis
基金
北京市医院管理中心临床医学发展专项(XMLX202146)
北京市通州区高层次人才发展支持计划领军人才(YHLD2019029)。
关键词
结核
肺
放射学
诊断
人工智能
综述文献(主题)
Tuberculosis,pulmonary
Radiology
Diagnosis
Artificial intelligence
Review literature as topic
