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 (3) , R. de Crevoisier (1, 2)

1 LTSI - Laboratoire Traitement du Signal et de l'Image
2 CRLCC - CRLCC Eugène Marquis
3 HES-SO - University of Applied Sciences and Arts of Western Switzerland

Domains: Life Sciences [q-bio]; Bioengineering

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 & Oncology, 2019, 133, pp.S525-S525. ⟨10.1016/S0167-8140(19)31385-4⟩. ⟨hal-02177168⟩