| Comparison of deep learning approaches for multi-label chest X-ray classification IM Baltruschat, H Nickisch, M Grass, T Knopp, A Saalbach Scientific reports 9 (1), 6381, 2019 | 440 | 2019 |
| Detection of suspicious lesions in dynamic contrast enhanced MRI data T Twellmann, A Saalbach, C Muller, TW Nattkemper, A Wismuller The 26th Annual International Conference of the IEEE Engineering in Medicine …, 2004 | 67 | 2004 |
| Libraries of synthetic stationary-phase and stress promoters as a tool for fine-tuning of expression of recombinant proteins in Escherichia coli G Miksch, F Bettenworth, K Friehs, E Flaschel, A Saalbach, T Twellmann, ... Journal of biotechnology 120 (1), 25-37, 2005 | 56 | 2005 |
| Continual learning for domain adaptation in chest x-ray classification M Lenga, H Schulz, A Saalbach Medical Imaging with Deep Learning, 413-423, 2020 | 55 | 2020 |
| Image fusion for dynamic contrast enhanced magnetic resonance imaging T Twellmann, A Saalbach, O Gerstung, MO Leach, TW Nattkemper Biomedical engineering online 3, 1-21, 2004 | 54 | 2004 |
| Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation I Baltruschat, L Steinmeister, H Nickisch, A Saalbach, M Grass, G Adam, ... European radiology 31, 3837-3845, 2021 | 45 | 2021 |
| Foveal fully convolutional nets for multi-organ segmentation T Brosch, A Saalbach Medical imaging 2018: Image processing 10574, 198-206, 2018 | 45 | 2018 |
| Correction of motion artifacts using a multiscale fully convolutional neural network K Sommer, A Saalbach, T Brosch, C Hall, NM Cross, JB Andre American Journal of Neuroradiology 41 (3), 416-423, 2020 | 39 | 2020 |
| Unsupervised clustering of fMRI and MRI time series A Meyer-Bäse, A Saalbach, O Lange, A Wismüller Biomedical Signal Processing and Control 2 (4), 295-310, 2007 | 36 | 2007 |
| Deep learning for pneumothorax detection and localization in chest radiographs A Gooßen, H Deshpande, T Harder, E Schwab, I Baltruschat, ... arXiv preprint arXiv:1907.07324, 2019 | 30 | 2019 |
| Sequential rib labeling and segmentation in chest X-ray using Mask R-CNN J Wessel, MP Heinrich, J von Berg, A Franz, A Saalbach arXiv preprint arXiv:1908.08329, 2019 | 29 | 2019 |
| When does bone suppression and lung field segmentation improve chest x-ray disease classification? IM Baltruschat, L Steinmeister, H Ittrich, G Adam, H Nickisch, A Saalbach, ... 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 29 | 2019 |
| A novel bone suppression method that improves lung nodule detection: Suppressing dedicated bone shadows in radiographs while preserving the remaining signal J von Berg, S Young, H Carolus, R Wolz, A Saalbach, A Hidalgo, ... International journal of computer assisted radiology and surgery 11, 641-655, 2016 | 28 | 2016 |
| A Hyperbolic Topographic Mapping for Proximity Data. A Saalbach, T Twellmann, TW Nattkemper, A Wismüller, J Ontrup, ... Artificial Intelligence and Applications 2005, 106-111, 2005 | 26 | 2005 |
| Optimized anatomical structure of interest labelling K Lu, A Groth, Y Qian, A Saalbach, RN Tellis, D Bystrov, R Cohen, ... US Patent 11,183,293, 2021 | 24 | 2021 |
| Localization of critical findings in chest X-ray without local annotations using multi-instance learning E Schwab, A Gooßen, H Deshpande, A Saalbach 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1879-1882, 2020 | 22 | 2020 |
| Automatic multi-model-based segmentation of the left atrium in cardiac MRI scans D Kutra, A Saalbach, H Lehmann, A Groth, SPM Dries, MW Krueger, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012: 15th …, 2012 | 21 | 2012 |
| Correction of motion artifacts using a multi-resolution fully convolutional neural network K Sommer, T Brosch, R Wiemker, T Harder, A Saalbach, CS Hall, ... Proceedings of the ISMRM Scientific Meeting & Exhibition, Paris 1175, 2018 | 19 | 2018 |
| Hand gesture recognition: self-organising maps as a graphical user interface for the partitioning of large training data sets G Heidemann, H Bekel, I Bax, A Saalbach Proceedings of the 17th International Conference on Pattern Recognition …, 2004 | 17 | 2004 |
| Parametrized SOMs for object recognition and pose estimation A Saalbach, G Heidemann, H Ritter International Conference on Artificial Neural Networks, 902-907, 2002 | 16 | 2002 |
