Christian F. Baumgartner
Christian F. Baumgartner
University of Tübingen & University of Lucerne
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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