Application of nnU-Net for Automatic Segmentation of Lung Lesions on CT Images and Its Implication for Radiomic Models

Application of nnU-Net for Automatic Segmentation of Lung Lesions on CT Images and Its Implication for Radiomic Models

Radiomics investigates the predictive role of quantitative parameters calculated from radiological images. In oncology, tumour segmentation constitutes a crucial step of the radiomic workflow. Manual segmentation is time-consuming and prone to inter-observer variability. In this study, a state-of-th...

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Bibliographic Details
Main Authors: Matteo Ferrante, Lisa Rinaldi, Francesca Botta, Xiaobin Hu, Andreas Dolp, Marta Minotti, Francesca De Piano, Gianluigi Funicelli, Stefania Volpe, Federica Bellerba, Paolo De Marco, Sara Raimondi, Stefania Rizzo, Kuangyu Shi, Marta Cremonesi, Barbara A. Jereczek-Fossa, Lorenzo Spaggiari, Filippo De Marinis, Roberto Orecchia, Daniela Origgi
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Journal of Clinical Medicine
Subjects:
nnU-Net
NSCLC
automatic segmentation
radiomics
hand-crafted/deep features
predictive model
Online Access:https://www.mdpi.com/2077-0383/11/24/7334

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https://www.mdpi.com/2077-0383/11/24/7334

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