| 18F-FDG PET maximum-intensity projections and artificial intelligence: a win-win combination to easily measure prognostic biomarkers in DLBCL patients KB Girum, L Rebaud, AS Cottereau, M Meignan, J Clerc, L Vercellino, ... Journal of Nuclear Medicine 63 (12), 1925-1932, 2022 | 24 | 2022 |
| Prognostic value of lesion dissemination in doxorubicin, bleomycin, vinblastine, and dacarbazine‐treated, interimPET‐negative classical Hodgkin Lymphoma patients: A radio … R Durmo, B Donati, L Rebaud, AS Cottereau, A Ruffini, ME Nizzoli, ... Hematological oncology 40 (4), 645-657, 2022 | 21 | 2022 |
| Simplicity is all you need: out-of-the-box nnUNet followed by binary-weighted radiomic model for segmentation and outcome prediction in head and neck PET/CT L Rebaud, T Escobar, F Khalid, K Girum, I Buvat 3D Head and Neck Tumor Segmentation in PET/CT Challenge, 121-134, 2022 | 13 | 2022 |
| Metabolic tumor volume predicts outcome in patients with advanced stage follicular lymphoma from the RELEVANCE trial AS Cottereau, L Rebaud, J Trotman, P Feugier, LJ Nastoupil, E Bachy, ... Annals of Oncology 35 (1), 130-137, 2024 | 4 | 2024 |
| Tumor location relative to the spleen is a prognostic factor in lymphoma patients: a demonstration from the REMARC trial KB Girum, AS Cottereau, L Vercellino, L Rebaud, J Clerc, O Casasnovas, ... Journal of Nuclear Medicine 65 (2), 313-319, 2024 | 2 | 2024 |
| Multitask learning-to-rank neural network for predicting survival of diffuse large B-cell lymphoma patients from their unsegmented baseline [18F] FDG-PET/CT scans. L Rebaud, N Capobianco, L Sibille, K Girum, M Meignan, AS Cottereau, ... Journal of Nuclear Medicine 63 (supplement 2), 3250-3250, 2022 | 2 | 2022 |
| Prognostic role of lesion dissemination feature (dmax) calculated on baseline pet/ct in hodgkin lymphoma R Durmo, A Ségolèn Cottereau, L Rebaud, C Nioche, A Ruffini, F Fioroni, ... Hematological Oncology 39, 2021 | 2 | 2021 |
| Evaluation of the prognostic value of tumor fragmentation on [18F]-FDG PET/CT on an independent cohort of diffuse large B-cell lymphoma patients L Rebaud, N Capobianco, L Sibille, K Girum, M Meignan, AS Cottereau, ... Journal of Nuclear Medicine 63 (supplement 2), 3172-3172, 2022 | 1 | 2022 |
| Scenarios where a signed binary (ICARE) model outperforms a Cox model for outcome prediction L Rebaud, N Capobianco, B Spottiswoode, I Buvat Journal of Nuclear Medicine 64 (supplement 1), P1218-P1218, 2023 | | 2023 |
| Multimodal risk assessment of Hodgkin lymphoma patients in a dual-center study D Haberl, K Girum, O Kulterer, AS Cottereau, Z Jiang, L Rebaud, A Flotats, ... Journal of Nuclear Medicine 64 (supplement 1), P1082-P1082, 2023 | | 2023 |
| Deep-learning-based 3D lesion segmentation on whole-body [18F]-FDG PET images including automated quality control: method and external validation K Girum, L Rebaud, AS Cottereau, T Escobar, J Clerc, L Vercellino, ... Journal of Nuclear Medicine 64 (supplement 1), P992-P992, 2023 | | 2023 |
| RADIOMICS REFLECTING BOTH TUMOR AND HOST FEATURES IMPROVES OUTCOME PREDICTION IN FOLLICULAR LYMPHOMA L Rebaud, N Capobianco, B Spottiswoode, A Cottereau, J Trotman, ... Hematological Oncology 41, 94-95, 2023 | | 2023 |
| Baseline PET Metabolic Tumor Volume Predicts Outcome in Advanced Follicular Lymphoma Patients Who Received First-Line Immunochemotherapy but Not Those Treated with Lenalidomide … AS Cottereau, L Rebaud, J Trotman, P Feugier, LJ Nastoupil, E Bachy, ... Blood 140 (Supplement 1), 6474-6476, 2022 | | 2022 |
| Stratification of Hodgkin lymphoma patients using metabolic tumor burden and tumor dissemination calculated from baseline [18F] FDG-PET/CT imaging K Girum, AS Cottereau, D Haberl, L Papp, L Rebaud, M Hacker, T Beyer, ... Journal of Nuclear Medicine 63 (supplement 2), 3123-3123, 2022 | | 2022 |
| Lesion dissemination feature (Dmax) calculated at baseline PET/CT improves risk stratification of ABVD treated Hodgkin Lymphoma patients R Durmo, A Cottereau, L Rebaud, C Nioche, A Ruffini, F Fioroni, ... EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 48 (SUPPL 1 …, 2021 | | 2021 |
| Head and Neck Tumor and Lymph Node Segmentation and Outcome Prediction from 18F-FDG PET/CT Images: Simplicity is All You Need L Rebaud, T Escobar, F Khalid, K Girum, I Buvat | | |
