Reproducibility of radiomic features in CT images of NSCLC patients: an integrative analysis on the impact of acquisition and reconstruction parameters

Reproducibility of radiomic features in CT images of NSCLC patients: an integrative analysis on the impact of acquisition and reconstruction parameters

Abstract Background We investigated to what extent tube voltage, scanner model, and reconstruction algorithm affect radiomic feature reproducibility in a single-institution retrospective database of computed tomography images of non-small-cell lung cancer patients. Methods This study was approved by...

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Bibliographic Details
Main Authors: Lisa Rinaldi, Simone P. De Angelis, Sara Raimondi, Stefania Rizzo, Cristiana Fanciullo, Cristiano Rampinelli, Manuel Mariani, Alessandro Lascialfari, Marta Cremonesi, Roberto Orecchia, Daniela Origgi, Francesca Botta
Format: Article
Language:English
Published: SpringerOpen 2022-01-01
Series:European Radiology Experimental
Subjects:
Carcinoma (non-small-cell lung)
Image processing (computer-assisted)
Machine learning
Reproducibility of results
Tomography (x-ray computed)
Online Access:https://doi.org/10.1186/s41747-021-00258-6

Internet

https://doi.org/10.1186/s41747-021-00258-6

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