Quantifying lung cancer heterogeneity using novel CT features: a cross-institute study

BACKGROUND: Radiomics-based image metrics are not used in the clinic despite the rapidly growing literature. We selected eight promising radiomic features and validated their value in decoding lung cancer heterogeneity. METHODS: CT images of 236 lung cancer patients were obtained from three differen...

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Detalles Bibliográficos
Autores principales: Wang, Zixing, Yang, Cuihong, Han, Wei, Sui, Xin, Zheng, Fuling, Xue, Fang, Xu, Xiaoli, Wu, Peng, Chen, Yali, Gu, Wentao, Song, Wei, Jiang, Jingmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050978/
https://www.ncbi.nlm.nih.gov/pubmed/35482262
http://dx.doi.org/10.1186/s13244-022-01204-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050978/
https://www.ncbi.nlm.nih.gov/pubmed/35482262
http://dx.doi.org/10.1186/s13244-022-01204-9

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