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Christoph Baur
Christoph Baur
Director Software Imaging Products at Rohde & Schwarz GmbH & Co. KG
Verified email at tum.de - Homepage
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Cited by
Year
Aggnet: deep learning from crowds for mitosis detection in breast cancer histology images
S Albarqouni, C Baur, F Achilles, V Belagiannis, S Demirci, N Navab
IEEE transactions on medical imaging 35 (5), 1313-1321, 2016
6802016
Deep autoencoding models for unsupervised anomaly segmentation in brain MR images
C Baur, B Wiestler, S Albarqouni, N Navab
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019
5672019
GANs for medical image analysis
S Kazeminia, C Baur, A Kuijper, B van Ginneken, N Navab, S Albarqouni, ...
Artificial intelligence in medicine 109, 101938, 2020
4592020
Staingan: Stain style transfer for digital histological images
MT Shaban, C Baur, N Navab, S Albarqouni
2019 Ieee 16th international symposium on biomedical imaging (Isbi 2019 …, 2019
3312019
Autoencoders for unsupervised anomaly segmentation in brain MR images: a comparative study
C Baur, S Denner, B Wiestler, N Navab, S Albarqouni
Medical Image Analysis 69, 101952, 2021
3212021
Semi-supervised deep learning for fully convolutional networks
C Baur, S Albarqouni, N Navab
Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017
1512017
Generating highly realistic images of skin lesions with GANs
C Baur, S Albarqouni, N Navab
OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy …, 2018
1152018
MelanoGANs: high resolution skin lesion synthesis with GANs
C Baur, S Albarqouni, N Navab
arXiv preprint arXiv:1804.04338, 2018
1092018
Steganomaly: Inhibiting cyclegan steganography for unsupervised anomaly detection in brain mri
C Baur, R Graf, B Wiestler, S Albarqouni, N Navab
International conference on medical image computing and computer-assisted …, 2020
512020
Scale-space autoencoders for unsupervised anomaly segmentation in brain mri
C Baur, B Wiestler, S Albarqouni, N Navab
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
402020
Modeling healthy anatomy with artificial intelligence for unsupervised anomaly detection in brain MRI
C Baur, B Wiestler, M Muehlau, C Zimmer, N Navab, S Albarqouni
Radiology: Artificial Intelligence 3 (3), e190169, 2021
382021
Fusing unsupervised and supervised deep learning for white matter lesion segmentation
C Baur, B Wiestler, S Albarqouni, N Navab
International Conference on Medical Imaging with Deep Learning, 63-72, 2019
332019
Bayesian skip-autoencoders for unsupervised hyperintense anomaly detection in high resolution brain MRI
C Baur, B Wiestler, S Albarqouni, N Navab
2020 IEEE 17th international symposium on biomedical imaging (ISBI), 1905-1909, 2020
322020
Adversarial networks for camera pose regression and refinement
M Bui, C Baur, N Navab, S Ilic, S Albarqouni
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
272019
Cathnets: detection and single-view depth prediction of catheter electrodes
C Baur, S Albarqouni, S Demirci, N Navab, P Fallavollita
Medical Imaging and Augmented Reality: 7th International Conference, MIAR …, 2016
202016
Automatic 3D reconstruction of electrophysiology catheters from two-view monoplane C-Arm image sequences
C Baur, F Milletari, V Belagiannis, N Navab, P Fallavollita
International Conference on Information Processing in Computer-Assisted …, 2015
152015
Robust navigation support in lowest dose image setting
M Bui, F Bourier, C Baur, F Milletari, N Navab, S Demirci
International journal of computer assisted radiology and surgery 14 (2), 291-300, 2019
52019
StainGAN: stain style transfer for digital histological images
M Tarek Shaban, C Baur, N Navab, S Albarqouni
arXiv e-prints, arXiv: 1804.01601, 2018
42018
Auxiliary manifold embedding for fully convolutional networks
C Baur, S Albarqouni, N Navab
arXiv preprint arXiv:1703.06000, 2017
32017
Adversarial Joint Image and Pose Distribution Learning for Camera Pose Regression and Refinement
M Bui, C Baur, N Navab, S Ilic, S Albarqouni
arXiv preprint arXiv:1903.06646, 2019
22019
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