| A deep metric for multimodal registration M Simonovsky, B Gutiérrez-Becker, D Mateus, N Navab, N Komodakis Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th …, 2016 | 246 | 2016 |
| Re-thinking the etiological framework of neurodegeneration X Castillo, S Castro-Obregón, B Gutiérrez-Becker, G Gutiérrez-Ospina, ... Frontiers in neuroscience 13, 728, 2019 | 68 | 2019 |
| Gaussian process uncertainty in age estimation as a measure of brain abnormality BG Becker, T Klein, C Wachinger, ... NeuroImage 175, 246-258, 2018 | 56 | 2018 |
| 3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation M Riva, C Hennersperger, F Milletari, A Katouzian, F Pessina, ... International journal of computer assisted radiology and surgery 12, 1711-1725, 2017 | 45 | 2017 |
| Automatic segmentation of the fetal cerebellum on ultrasound volumes, using a 3D statistical shape model B Gutiérrez-Becker, F Arámbula Cosío, ME Guzmán Huerta, ... Medical & biological engineering & computing 51, 1021-1030, 2013 | 30 | 2013 |
| Training and deploying a deep learning model for endoscopic severity grading in ulcerative colitis using multicenter clinical trial data B Gutierrez Becker, F Arcadu, A Thalhammer, C Gamez Serna, O Feehan, ... Therapeutic advances in gastrointestinal endoscopy 14, 2631774521990623, 2021 | 25 | 2021 |
| A wide and deep neural network for survival analysis from anatomical shape and tabular clinical data S Pölsterl, I Sarasua, B Gutiérrez-Becker, C Wachinger Machine Learning and Knowledge Discovery in Databases: International …, 2020 | 25 | 2020 |
| Automatic segmentation of the cerebellum of fetuses on 3D ultrasound images, using a 3D Point Distribution Model BG Becker, FA Cosío, MEG Huerta, JA Benavides-Serralde 2010 Annual International Conference of the IEEE Engineering in Medicine and …, 2010 | 25 | 2010 |
| Quantifying confounding bias in neuroimaging datasets with causal inference C Wachinger, BG Becker, A Rieckmann, S Pölsterl Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 24 | 2019 |
| Deep multi-structural shape analysis: application to neuroanatomy B Gutiérrez-Becker, C Wachinger Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 24 | 2018 |
| Learning optimization updates for multimodal registration B Gutiérrez-Becker, D Mateus, L Peter, N Navab Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th …, 2016 | 24 | 2016 |
| Guiding multimodal registration with learned optimization updates B Gutierrez-Becker, D Mateus, L Peter, N Navab Medical image analysis 41, 2-17, 2017 | 23 | 2017 |
| Discriminative and generative models for anatomical shape analysis on point clouds with deep neural networks B Gutiérrez-Becker, I Sarasua, C Wachinger Medical Image Analysis 67, 101852, 2021 | 9 | 2021 |
| A multi-armed bandit to smartly select a training set from big medical data B Gutiérrez, L Peter, T Klein, C Wachinger Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 9 | 2017 |
| Hands-free segmentation of medical volumes via binary inputs F Dubost, L Peter, C Rupprecht, BG Becker, N Navab Deep Learning and Data Labeling for Medical Applications: First …, 2016 | 8 | 2016 |
| Learning a conditional generative model for anatomical shape analysis B Gutiérrez-Becker, C Wachinger Information Processing in Medical Imaging: 26th International Conference …, 2019 | 7 | 2019 |
| Spatial compounding of 3-D fetal brain ultrasound using probabilistic maps J Perez-Gonzalez, F Arámbula-Cosío, M Guzmán, L Camargo, ... Ultrasound in Medicine & Biology 44 (1), 278-291, 2018 | 7 | 2018 |
| Detect, quantify, and incorporate dataset bias: A neuroimaging analysis on 12,207 individuals C Wachinger, BG Becker, A Rieckmann arXiv preprint arXiv:1804.10764, 2018 | 6 | 2018 |
| A sparse approach to build shape models with routine clinical data B Gutierrez, D Mateus, E Shiban, B Meyer, J Lehmberg, N Navab 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 258-261, 2014 | 6 | 2014 |
| Prediction of Fluid Intelligence from T1-Weighted Magnetic Resonance Images S Pölsterl, B Gutiérrez-Becker, I Sarasua, A Guha Roy, C Wachinger Adolescent Brain Cognitive Development Neurocognitive Prediction: First …, 2019 | 3 | 2019 |
Nassir NavabProfessor of Computer Science, Technische Universität MünchenDirección de correo verificada de cs.tum.edu
