| Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved? O Bernard, A Lalande, C Zotti, F Cervenansky, X Yang, PA Heng, I Cetin, ... IEEE transactions on medical imaging 37 (11), 2514-2525, 2018 | 1806 | 2018 |
| Unsupervised domain adaptation in brain lesion segmentation with adversarial networks K Kamnitsas, C Baumgartner, C Ledig, V Newcombe, J Simpson, A Kane, ... Information Processing in Medical Imaging: 25th International Conference …, 2017 | 588 | 2017 |
| SonoNet: real-time detection and localisation of fetal standard scan planes in freehand ultrasound CF Baumgartner, K Kamnitsas, J Matthew, TP Fletcher, S Smith, LM Koch, ... IEEE transactions on medical imaging 36 (11), 2204-2215, 2017 | 388 | 2017 |
| An exploration of 2D and 3D deep learning techniques for cardiac MR image segmentation CF Baumgartner, LM Koch, M Pollefeys, E Konukoglu International Workshop on Statistical Atlases and Computational Models of …, 2017 | 318 | 2017 |
| PHiSeg: Capturing uncertainty in medical image segmentation CF Baumgartner, KC Tezcan, K Chaitanya, AM Hötker, UJ Muehlematter, ... International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 240 | 2019 |
| Visual feature attribution using Wasserstein GANs CF Baumgartner, LM Koch, K Can Tezcan, J Xi Ang, E Konukoglu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 186 | 2018 |
| Semi-supervised and task-driven data augmentation K Chaitanya, N Karani, CF Baumgartner, A Becker, O Donati, ... Information Processing in Medical Imaging: 26th International Conference …, 2019 | 180 | 2019 |
| A lifelong learning approach to brain MR segmentation across scanners and protocols N Karani, K Chaitanya, C Baumgartner, E Konukoglu International conference on medical image computing and computer-assisted …, 2018 | 146 | 2018 |
| MR image reconstruction using deep density priors KC Tezcan, CF Baumgartner, R Luechinger, KP Pruessmann, ... IEEE transactions on medical imaging 38 (7), 1633-1642, 2018 | 135 | 2018 |
| Semi-supervised task-driven data augmentation for medical image segmentation K Chaitanya, N Karani, CF Baumgartner, E Erdil, A Becker, O Donati, ... Medical Image Analysis 68, 101934, 2021 | 126 | 2021 |
| Learning to segment medical images with scribble-supervision alone YB Can, K Chaitanya, B Mustafa, LM Koch, E Konukoglu, ... Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018 | 113 | 2018 |
| A partially reversible U-Net for memory-efficient volumetric image segmentation R Brügger, CF Baumgartner, E Konukoglu Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 100 | 2019 |
| Real-time standard scan plane detection and localisation in fetal ultrasound using fully convolutional neural networks CF Baumgartner, K Kamnitsas, J Matthew, S Smith, B Kainz, D Rueckert Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 90 | 2016 |
| Human-level performance on automatic head biometrics in fetal ultrasound using fully convolutional neural networks M Sinclair, CF Baumgartner, J Matthew, W Bai, JC Martinez, Y Li, S Smith, ... 2018 40th annual international conference of the IEEE engineering in …, 2018 | 73 | 2018 |
| Automated detection of motion artefacts in MR imaging using decision forests B Lorch, G Vaillant, C Baumgartner, W Bai, D Rueckert, A Maier Journal of medical engineering 2017 (1), 4501647, 2017 | 63 | 2017 |
| Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain J Kemnitz, CF Baumgartner, F Eckstein, A Chaudhari, A Ruhdorfer, ... Magnetic Resonance Materials in Physics, Biology and Medicine 33, 483-493, 2020 | 55 | 2020 |
| High-resolution dynamic MR imaging of the thorax for respiratory motion correction of PET using groupwise manifold alignment CF Baumgartner, C Kolbitsch, DR Balfour, PK Marsden, JR McClelland, ... Medical image analysis 18 (7), 939-952, 2014 | 51 | 2014 |
| Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control E Puyol-Antón, B Ruijsink, CF Baumgartner, PG Masci, M Sinclair, ... Journal of Cardiovascular Magnetic Resonance 22 (1), 60, 2020 | 42 | 2020 |
| Autoadaptive motion modelling for MR-based respiratory motion estimation CF Baumgartner, C Kolbitsch, JR McClelland, D Rueckert, AP King Medical image analysis 35, 83-100, 2017 | 41 | 2017 |
| A unified tractography framework for comparing diffusion models on clinical scans C Baumgartner, O Michailovich, J Levitt, O Pasternak, S Bouix, CF Westin, ... Computational Diffusion MRI Workshop of MICCAI, Nice, 27-32, 2012 | 37 | 2012 |
Ender KonukogluETH ZurichVerified email at vision.ee.ethz.ch
