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Journal articles
How to find the best radiomics features for prediction of overall survival in SBRT for HCC?
P. Fontaine
1, 2
Oscar Acosta
1, 2
F. Riet
1, 2
J. Castelli
1, 2
K. Gnep
1, 2
A. Simon
1, 2
A. Depeursinge
R. de Crevoisier
1, 2
1
LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - Bât 22 - 35042 Rennes - France)
- UR1 - Université de Rennes 1 (2 rue du Thabor - CS 46510 - 35065 Rennes cedex - France)
- UNIV-RENNES - Université de Rennes (France)
- INSERM - Institut National de la Santé et de la Recherche Médicale : U1099 (101, rue de Tolbiac, 75013 Paris - France)
2
CRLCC - CRLCC Eugène Marquis (Avenue Bataille Flandres-Dunkerque 35042 RENNES CEDEX - France)
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Complete list of metadatas
https://hal-univ-rennes1.archives-ouvertes.fr/hal-02177168
Contributor : Laurent Jonchère <>
Submitted on : Monday, July 8, 2019 - 4:42:40 PM
Last modification on : Friday, January 24, 2020 - 2:38:37 PM
Contributor : Laurent Jonchère <>
Submitted on : Monday, July 8, 2019 - 4:42:40 PM
Last modification on : Friday, January 24, 2020 - 2:38:37 PM
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Identifiers
- HAL Id : hal-02177168, version 1
- DOI : 10.1016/S0167-8140(19)31385-4
Collections
LTSI | UNIV-RENNES1 | MARQUIS | FNCLCC | UNIV-RENNES
Citation
P. Fontaine, Oscar Acosta, F. Riet, J. Castelli, K. Gnep, et al.. How to find the best radiomics features for prediction of overall survival in SBRT for HCC?. Radiotherapy and Oncology, Elsevier, 2019, 133, pp.S525-S525. ⟨10.1016/S0167-8140(19)31385-4⟩. ⟨hal-02177168⟩
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