| Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge VM Campello, P Gkontra, C Izquierdo, C Martin-Isla, A Sojoudi, PM Full, ... IEEE Transactions on Medical Imaging 40 (12), 3543-3554, 2021 | 222 | 2021 |
| Radiomic versus convolutional neural networks analysis for classification of contrast-enhancing lesions at multiparametric breast MRI D Truhn, S Schrading, C Haarburger, H Schneider, D Merhof, C Kuhl Radiology 290 (2), 290-297, 2019 | 198 | 2019 |
| Radiomics feature reproducibility under inter-rater variability in segmentations of CT images C Haarburger, G Müller-Franzes, L Weninger, C Kuhl, D Truhn, D Merhof Scientific Reports 10 (1), 1-10, 2020 | 80 | 2020 |
| Image-Based Survival Prediction for Lung Cancer Patients Using CNNS C Haarburger, P Weitz, O Rippel, D Merhof 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 47 | 2019 |
| Diffusion MRI signal augmentation: from single shell to multi shell with deep learning S Koppers, C Haarburger, D Merhof International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 40 | 2017 |
| Breaking medical data sharing boundaries by using synthesized radiographs T Han, S Nebelung, C Haarburger, N Horst, S Reinartz, D Merhof, ... Science Advances 6 (49), eabb7973, 2020 | 38 | 2020 |
| Diffusion Probabilistic Models beat GANs on Medical Images G Müller-Franzes, JM Niehues, F Khader, ST Arasteh, C Haarburger, ... arXiv preprint arXiv:2212.07501, 2022 | 31 | 2022 |
| Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification C Haarburger, M Baumgartner, D Truhn, M Broeckmann, H Schneider, ... Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019 | 26 | 2019 |
| Medical Diffusion--Denoising Diffusion Probabilistic Models for 3D Medical Image Generation F Khader, G Mueller-Franzes, ST Arasteh, T Han, C Haarburger, ... arXiv preprint arXiv:2211.03364, 2022 | 22 | 2022 |
| Robustness of radiomics for survival prediction of brain tumor patients depending on resection status L Weninger, C Haarburger, D Merhof Frontiers in computational neuroscience 13, 73, 2019 | 22 | 2019 |
| Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization T Han, S Nebelung, F Pedersoli, M Zimmermann, M Schulze-Hagen, ... Nature Communications 12 (1), 1-11, 2021 | 21 | 2021 |
| Transfer Learning for Breast Cancer Malignancy Classification based on Dynamic Contrast-Enhanced MR Images C Haarburger, P Langenberg, D Truhn, H Schneider, J Thüring, ... Bildverarbeitung für die Medizin (BVM), 2018 | 18 | 2018 |
| Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks. C Haarburger, N Horst, D Truhn, M Broeckmann, S Schrading, C Kuhl, ... VCBM, 11-15, 2019 | 17 | 2019 |
| Denoising diffusion probabilistic models for 3D medical image generation F Khader, G Müller-Franzes, S Tayebi Arasteh, T Han, C Haarburger, ... Scientific Reports 13 (1), 7303, 2023 | 15 | 2023 |
| Artificial intelligence for clinical interpretation of bedside chest radiographs F Khader, T Han, G Müller-Franzes, L Huck, P Schad, S Keil, E Barzakova, ... Radiology, 220510, 2022 | 13 | 2022 |
| Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach J Thüring, O Rippel, C Haarburger, D Merhof, P Schad, P Bruners, ... European radiology experimental 4 (1), 1-9, 2020 | 13 | 2020 |
| Adaptive preprocessing for generalization in cardiac MR image segmentation F Khader, J Schock, D Truhn, F Morsbach, C Haarburger International Workshop on Statistical Atlases and Computational Models of …, 2021 | 8 | 2021 |
| Towards an algorithm for automatic accelerometer-based pulse presence detection during cardiopulmonary resuscitation K Dellimore, R Wijshoff, C Haarburger, V Aarts, R Derkx, J van de Laar, ... 2016 38th Annual International Conference of the IEEE Engineering in …, 2016 | 8 | 2016 |
| Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation T Han, JN Kather, F Pedersoli, M Zimmermann, S Keil, M Schulze-Hagen, ... Nature Machine Intelligence, 1-11, 2022 | 7 | 2022 |
| Elevating Fundoscopic Evaluation to Expert Level-Automatic Glaucoma Detection Using Data from the Airogs Challenge F Khader, C Haarburger, JC Kirr, M Menke, JN Kather, J Stegmaier, ... 2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC), 1-4, 2022 | 6 | 2022 |
Daniel TruhnOberarzt Radiologie, UK AachenBestätigte E-Mail-Adresse bei ukaachen.de
