摘要
肺血栓栓塞症(PTE)是一组由内源性或外源性栓子造成呼吸和循环系统障碍的病理生理综合征,需要及时诊断和改善预后。基于CT影像的深度学习(DL)能够深度挖掘分析PTE疾病特征,在制定诊疗策略和评估血栓负荷等方面具有重要作用。就基于CT影像的DL在PTE中的应用进展予以综述。
Pulmonary thromboembolism(PTE)is a group of pathophysiological with respiratory and circulatory disorders syndromes caused by endogenous or exogenous emboli that require timely diagnosis and improved prognosis.Deep learning based on CT can deeply analyze PTE disease characteristics and plays an important role in the formulation of PTE diagnosis and treatment strategies,as well as the evaluation of thrombus burden.This paper summarizes the application value and progress of deep learning based on CT images in PTE.
作者
陈蓉
杨越
于雅茜
杨飞(审校)
CHEN Rong;YANG Yue;YU Yaxi;YANG Fei(Graduate Faculty,Hebei North University,Zhangjiakou 075000,China;Department of Medical Imaging,The First Affiliated Hospital of Hebei North University)
出处
《国际医学放射学杂志》
2024年第2期219-222,共4页
International Journal of Medical Radiology
基金
河北省省级科技计划项目(21377769D)。
关键词
肺血栓栓塞症
CT肺动脉成像
深度学习
Pulmonary thromboembolism
CT pulmonary angiography
Deep learning
