The authors of this article would like to point out that funding information was accidentally omitted.
The text as it should have appeared is below:
Funding
This work was supported by the Swiss Personalized Health Network (SPHN, via the IMAGINE project).
The authors apologise for this omission.
Article info
Publication history
Published online: June 23, 2022
Identification
Copyright
© 2022 The Author(s). Published by Elsevier B.V. on behalf of European Society of Radiotherapy & Oncology.
User license
Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0) | How you can reuse 
Elsevier's open access license policy
Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0)
Permitted
For non-commercial purposes:
- Read, print & download
- Redistribute or republish the final article
- Text & data mine
- Translate the article (private use only, not for distribution)
- Reuse portions or extracts from the article in other works
Not Permitted
- Sell or re-use for commercial purposes
- Distribute translations or adaptations of the article
Elsevier's open access license policy
ScienceDirect
Access this article on ScienceDirectLinked Article
- Robustness of radiomic features in magnetic resonance imaging for patients with glioblastoma: Multi-center studyPhysics and Imaging in Radiation OncologyVol. 22
- PreviewRadiomics offers great potential in improving diagnosis and treatment for patients with glioblastoma multiforme. However, in order to implement radiomics in clinical routine, the features used for prognostic modelling need to be stable. This comprises significant challenge in multi-center studies. The aim of this study was to evaluate the impact of different image normalization methods on MRI features robustness in multi-center study.
- Full-Text
- Preview
