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
2 CRLCC - CRLCC Eugène Marquis
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-02177168
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Submitted on : Monday, July 8, 2019 - 4:42:40 PM
Last modification on : Friday, November 8, 2019 - 1:23:05 PM

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LTSI | UNIV-RENNES1 | MARQUIS | FNCLCC | UNIV-RENNES

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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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