| Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge A Lalande, Z Chen, T Pommier, T Decourselle, A Qayyum, M Salomon, ... Medical Image Analysis 79, 102428, 2022 | 37 | 2022 |
| Fast interactive medical image segmentation with weakly supervised deep learning method KB Girum, G Créhange, R Hussain, A Lalande International Journal of Computer Assisted Radiology and Surgery 15, 1437-1444, 2020 | 36 | 2020 |
| Learning with context feedback loop for robust medical image segmentation KB Girum, G Créhange, A Lalande IEEE transactions on medical imaging 40 (6), 1542-1554, 2021 | 35 | 2021 |
| A deep learning method for real-time intraoperative US image segmentation in prostate brachytherapy KB Girum, A Lalande, R Hussain, G Créhange International Journal of Computer Assisted Radiology and Surgery 15 (9 …, 2020 | 30 | 2020 |
| 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 | 21 | 2022 |
| Automatic segmentation of inner ear on CT-scan using auto-context convolutional neural network R Hussain, A Lalande, KB Girum, C Guigou, A Bozorg Grayeli Scientific Reports 11 (1), 4406, 2021 | 19 | 2021 |
| Augmented reality for inner ear procedures: visualization of the cochlear central axis in microscopic videos R Hussain, A Lalande, K Berihu Girum, C Guigou, AB Grayeli International Journal of Computer Assisted Radiology and Surgery 15 (10 …, 2020 | 16 | 2020 |
| Real-time augmented reality for ear surgery R Hussain, A Lalande, R Marroquin, KB Girum, C Guigou, AB Grayeli Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 15 | 2018 |
| 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 | 12 | 2022 |
| Automatic myocardial infarction evaluation from delayed-enhancement cardiac MRI using deep convolutional networks KB Girum, Y Skandarani, R Hussain, AB Grayeli, G Créhange, A Lalande Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC …, 2021 | 10 | 2021 |
| Deep generative model-driven multimodal prostate segmentation in radiotherapy KB Girum, G Créhange, R Hussain, PM Walker, A Lalande Artificial Intelligence in Radiation Therapy: First International Workshop …, 2019 | 10 | 2019 |
| Inferring postimplant dose distribution of salvage permanent prostate implant (PPI) after primary PPI on CT images KB Girum, A Lalande, M Quivrin, I Bessières, N Pierrat, E Martin, ... Brachytherapy 17 (6), 866-873, 2018 | 8 | 2018 |
| 3D landmark detection for augmented reality based otologic procedures R Hussain, A Lalande, KB Girum, C Guigou, AB Grayeli arXiv preprint arXiv:1909.01647, 2019 | 3 | 2019 |
| 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 |
| Federated testing of AI techniques: Towards sharing of implementations, not just code F Yousefirizi, I Klyuzhin, K Girum, C Uribe, I Buvat, A Rahmim Journal of Nuclear Medicine 64 (supplement 1), P1482-P1482, 2023 | 1 | 2023 |
| 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 |
| 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 | | 2024 |
| Application of deep learning and machine learning methods to predict NSCLC patients’ survival from baseline 18F-FDG PET images TK Le, C David, S Contu, F Hugonnet, M Bauckneht, J Otto, K Girum, ... Journal of Nuclear Medicine 64 (supplement 1), P883-P883, 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 |
