Objects
Largent, Axel, Nunes, Jean-Claude, de Crevoisier, Renaud, Acosta, Oscar, Saint-Jalmes, Hervé, Simon, Antoine, Perichon, Nicholas, Barateau, Anais, Hervé, Chloé, Lafond, Caroline, Greer, Peter B., Dowling, Jason A.. Institute of Electrical and Electronics Engineers (IEEE); 2017. Pseudo-CT generation by conditional inference random forest for MRI-based radiotherapy treatment planning.
Largent, Axel, Nunes, Jean-Claude, Saint-Jalmes, Hervé, Baxter, John, Greer, Peter, Dowling, Jason, de Crevoisier, Renaud, Acosta, Oscar. IEEE; 2019. Pseudo-CT generation for MRI-only radiotherapy: comparative study between a generative adversarial network, a U-Net network, a patch-based, and an atlas based methods.
Mylona, Eugenia, Ebert, Martin, Kennedy, Angel, Joseph, David, Denham, James, Steigler, Allison, Supiot, Stephane, Acosta, Oscar, de Crevoisier, Renaud. Elsevier; 2020. Rectal and Urethro-Vesical Subregions for Toxicity Prediction After Prostate Cancer Radiation Therapy: Validation of Voxel-Based Models in an Independent Population.
Largent, Axel, Barateau, Anaïs, Nunes, Jean-Claude, Lafond, Caroline, Greer, Peter B., Dowling, Jason A., Saint-Jalmes, Hervé, Acosta, Oscar, de Crevoisier, Renaud. Elsevier; 2019. Pseudo-CT generation for MRI-only radiation therapy treatment planning: comparison among patch-based, atlas-based, and bulk density methods.
Largent, Axel, Barateau, Anais, Nunes, Jean-Claude, Mylona, Eugenia, Castelli, Joel, Lafond, Caroline, Greer, Peter B., Dowling, Jason A., Baxter, John, Saint-Jalmes, Herve, Acosta, Oscar, de Crevoisier, Renaud. Elsevier Inc.; 2019. Comparison of deep learning-based and patch-based methods for pseudo-CT generation in MRI-based prostate dose planning.