| Literature DB >> 31991420 |
Turkey Refaee1,2, Guangyao Wu3, Abdallah Ibrahim3,4,5,6, Iva Halilaj3, Ralph T H Leijenaar3, William Rogers3,7, Hester A Gietema4, Lizza E L Hendriks8, Philippe Lambin3,4, Henry C Woodruff3,4.
Abstract
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.Entities:
Keywords: Chronic obstructive pulmonary disease; Lung cancer; Radiomics
Mesh:
Year: 2020 PMID: 31991420 PMCID: PMC7949220 DOI: 10.1159/000505429
Source DB: PubMed Journal: Respiration ISSN: 0025-7931 Impact factor: 3.580