Impact of Interobserver Variability in Manual Segmentation of Non-Small Cell Lung Cancer (NSCLC) Applying Low-Rank Radiomic Representation on Computed Tomography

SIMPLE SUMMARY: Discovery of predictive and prognostic radiomic features in cancer is currently of great interest to the radiologic and oncologic community. Tumor phenotypic and prognostic information can be obtained by extracting features on tumor segmentations, and it is typically imaging analysts...

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Detalles Bibliográficos
Autores principales: Hershman, Michelle, Yousefi, Bardia, Serletti, Lacey, Galperin-Aizenberg, Maya, Roshkovan, Leonid, Luna, José Marcio, Thompson, Jeffrey C., Aggarwal, Charu, Carpenter, Erica L., Kontos, Despina, Katz, Sharyn I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657389/
https://www.ncbi.nlm.nih.gov/pubmed/34885094
http://dx.doi.org/10.3390/cancers13235985

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657389/
https://www.ncbi.nlm.nih.gov/pubmed/34885094
http://dx.doi.org/10.3390/cancers13235985

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