无线电技术
医学
慢性阻塞性肺病
肺癌
肺
工作流程
肺病
医学影像学
重症监护医学
癌症
病理
肿瘤科
放射科
医学物理学
内科学
数据库
计算机科学
作者
Turkey Refaee,Guangyao Wu,Abdalla Ibrahim,Iva Halilaj,Ralph T. H. Leijenaar,William Rogers,Hester A. Gietema,Lizza Hendriks,Philippe Lambin,Henry C. Woodruff
出处
期刊:Respiration
[Karger Publishers]
日期:2020-01-01
卷期号:99 (2): 99-107
被引量:43
摘要
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineable data, by extracting and correlating quantitative imaging features with patients’ outcomes and tumor phenotype – a process termed radiomics. While this process has already been widely researched in lung oncology, the evaluation of COPD in this fashion remains in its infancy. Here we outline the main applications of radiomics in lung cancer and briefly review the workflow from image acquisition to the evaluation of model performance. Finally, we discuss the current assessments of COPD and the potential application of radiomics in COPD.
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