| Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem J Hofmanninger, F Prayer, J Pan, S Röhrich, H Prosch, G Langs European radiology experimental 4, 1-13, 2020 | 557* | 2020 |
| Machine learning: from radiomics to discovery and routine G Langs, S Röhrich, J Hofmanninger, F Prayer, J Pan, C Herold, H Prosch Der Radiologe 58 (Suppl 1), 1-6, 2018 | 90 | 2018 |
| Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging M Perkonigg, J Hofmanninger, CJ Herold, JA Brink, O Pianykh, H Prosch, ... Nature communications 12 (1), 5678, 2021 | 79 | 2021 |
| Mapping visual features to semantic profiles for retrieval in medical imaging J Hofmanninger, G Langs Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 51 | 2015 |
| Dynamic memory to alleviate catastrophic forgetting in continuous learning settings J Hofmanninger, M Perkonigg, JA Brink, O Pianykh, C Herold, G Langs Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 32 | 2020 |
| Variability of computed tomography radiomics features of fibrosing interstitial lung disease: A test-retest study F Prayer, J Hofmanninger, M Weber, D Kifjak, A Willenpart, J Pan, ... Methods 188, 98-104, 2021 | 31 | 2021 |
| Artificial intelligence in lung imaging F Prayer, S Röhrich, J Pan, J Hofmanninger, G Langs, H Prosch Der Radiologe 60, 42-47, 2020 | 25 | 2020 |
| Continual active learning for efficient adaptation of machine learning models to changing image acquisition M Perkonigg, J Hofmanninger, G Langs International Conference on Information Processing in Medical Imaging, 649-660, 2021 | 24 | 2021 |
| AIX-COVNET M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ... Common pitfalls and recommendations for using machine learning to detect and …, 2021 | 22 | 2021 |
| Volumetry based biomarker speed of growth: Quantifying the change of total tumor volume in whole-body magnetic resonance imaging over time improves risk stratification of … M Wennmann, L Kintzelé, M Piraud, BH Menze, T Hielscher, ... Oncotarget 9 (38), 25254, 2018 | 21 | 2018 |
| Unsupervised machine learning identifies predictive progression markers of IPF J Pan, J Hofmanninger, KH Nenning, F Prayer, S Röhrich, N Sverzellati, ... European radiology 33 (2), 925-935, 2023 | 19 | 2023 |
| Radiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma S Röhrich, J Hofmanninger, L Negrin, G Langs, H Prosch European radiology 31, 5443-5453, 2021 | 19 | 2021 |
| Unsupervised identification of clinically relevant clusters in routine imaging data J Hofmanninger, M Krenn, M Holzer, T Schlegl, H Prosch, G Langs Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 19 | 2016 |
| Prospects and challenges of radiomics by using nononcologic routine chest CT S Röhrich, J Hofmanninger, F Prayer, H Müller, H Prosch, G Langs Radiology: Cardiothoracic Imaging 2 (4), e190190, 2020 | 18 | 2020 |
| Effects of individualized electrical impedance tomography and image reconstruction settings upon the assessment of regional ventilation distribution: Comparison to 4 … F Thürk, S Boehme, D Mudrak, S Kampusch, A Wielandner, H Prosch, ... PLoS One 12 (8), e0182215, 2017 | 17 | 2017 |
| Heterogeneity and matching of ventilation and perfusion within anatomical lung units in rats RW Glenny, C Bauer, J Hofmanninger, WJ Lamm, MA Krueger, ... Respiratory physiology & neurobiology 189 (3), 594-606, 2013 | 15 | 2013 |
| Detecting bone lesions in multiple myeloma patients using transfer learning M Perkonigg, J Hofmanninger, B Menze, MA Weber, G Langs Data Driven Treatment Response Assessment and Preterm, Perinatal, and …, 2018 | 13 | 2018 |
| Künstliche Intelligenz in der Bildgebung der Lunge. F Prayer, S Röhrich, J Pan, J Hofmanninger, G Langs, H Prosch Der Radiologe 60 (1), 2020 | 9 | 2020 |
| Continual active learning using pseudo-domains for limited labelling resources and changing acquisition characteristics M Perkonigg, J Hofmanninger, C Herold, H Prosch, G Langs arXiv preprint arXiv:2111.13069, 2021 | 7 | 2021 |
| Maschinelles Lernen in der Radiologie: Begriffsbestimmung vom Einzelzeitpunkt bis zur Trajektorie. G Langs, U Attenberger, R Licandro, J Hofmanninger, M Perkonigg, ... Der Radiologe 60 (1), 2020 | 7 | 2020 |
Georg LangsMedical University of Vienna, CIR LabVerified email at meduniwien.ac.at
