| Unsupervised anomaly detection with generative adversarial networks to guide marker discovery T Schlegl, P Seeböck, SM Waldstein, U Schmidt-Erfurth, G Langs International conference on information processing in medical imaging, 146-157, 2017 | 3022 | 2017 |
| Situating the default-mode network along a principal gradient of macroscale cortical organization DS Margulies, SS Ghosh, A Goulas, M Falkiewicz, JM Huntenburg, ... Proceedings of the National Academy of Sciences 113 (44), 12574-12579, 2016 | 1786 | 2016 |
| Causability and explainability of artificial intelligence in medicine A Holzinger, G Langs, H Denk, K Zatloukal, H Müller Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9 (4 …, 2019 | 1497 | 2019 |
| f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks T Schlegl, P Seeböck, SM Waldstein, G Langs, U Schmidt-Erfurth Medical image analysis 54, 30-44, 2019 | 1362 | 2019 |
| Introduction to radiomics ME Mayerhoefer, A Materka, G Langs, I Häggström, P Szczypiński, ... Journal of Nuclear Medicine 61 (4), 488-495, 2020 | 1194 | 2020 |
| Fully automated detection and quantification of macular fluid in OCT using deep learning T Schlegl, SM Waldstein, H Bogunovic, F Endstraßer, A Sadeghipour, ... Ophthalmology 125 (4), 549-558, 2018 | 552 | 2018 |
| Parcellating cortical functional networks in individuals D Wang, RL Buckner, MD Fox, DJ Holt, AJ Holmes, S Stoecklein, G Langs, ... Nature neuroscience 18 (12), 1853-1860, 2015 | 499 | 2015 |
| 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), 1-13, 2020 | 468 | 2020 |
| BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets R Vos de Wael, O Benkarim, C Paquola, S Lariviere, J Royer, S Tavakol, ... Communications biology 3 (1), 103, 2020 | 412 | 2020 |
| The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space J Klughammer, B Kiesel, T Roetzer, N Fortelny, A Nemc, KH Nenning, ... Nature medicine 24 (10), 1611-1624, 2018 | 281 | 2018 |
| Fast active appearance model search using canonical correlation analysis R Donner, M Reiter, G Langs, P Peloschek, H Bischof Pattern Analysis and Machine Intelligence, IEEE Transactions on 28 (10 …, 2006 | 231 | 2006 |
| The prenatal origin of hemispheric asymmetry: an in utero neuroimaging study G Kasprian, G Langs, PC Brugger, M Bittner, M Weber, M Arantes, ... Cerebral cortex 21 (5), 1076-1083, 2011 | 214 | 2011 |
| Machine learning to analyze the prognostic value of current imaging biomarkers in neovascular age-related macular degeneration U Schmidt-Erfurth, H Bogunovic, A Sadeghipour, T Schlegl, G Langs, ... Ophthalmology Retina 2 (1), 24-30, 2018 | 209 | 2018 |
| Cloud-based evaluation of anatomical structure segmentation and landmark detection algorithms: VISCERAL anatomy benchmarks O Jimenez-del-Toro, H Müller, M Krenn, K Gruenberg, AA Taha, ... IEEE transactions on medical imaging 35 (11), 2459-2475, 2016 | 204 | 2016 |
| Continuous learning AI in radiology: implementation principles and early applications OS Pianykh, G Langs, M Dewey, DR Enzmann, CJ Herold, ... Radiology 297 (1), 6-14, 2020 | 185 | 2020 |
| Prediction of anti-VEGF treatment requirements in neovascular AMD using a machine learning approach H Bogunović, SM Waldstein, T Schlegl, G Langs, A Sadeghipour, X Liu, ... Investigative ophthalmology & visual science 58 (7), 3240-3248, 2017 | 185 | 2017 |
| Cross-species functional alignment reveals evolutionary hierarchy within the connectome T Xu, KH Nenning, E Schwartz, SJ Hong, JT Vogelstein, A Goulas, ... NeuroImage, 117346, 2020 | 179 | 2020 |
| Exploiting epistemic uncertainty of anatomy segmentation for anomaly detection in retinal OCT P Seeböck, JI Orlando, T Schlegl, SM Waldstein, H Bogunović, ... IEEE transactions on medical imaging 39 (1), 87-98, 2019 | 164 | 2019 |
| Predicting semantic descriptions from medical images with convolutional neural networks T Schlegl, SM Waldstein, WD Vogl, U Schmidt-Erfurth, G Langs International Conference on Information Processing in Medical Imaging, 437-448, 2015 | 162 | 2015 |
| Fetal functional imaging portrays heterogeneous development of emerging human brain networks A Jakab, E Schwartz, G Kasprian, GM Gruber, D Prayer, V Schöpf, ... Frontiers in human neuroscience 8, 852, 2014 | 149 | 2014 |
Sebastian M. WaldsteinOphthalmology, Landesklinikum Mistelbach-GänserndorfVerified email at meduniwien.ac.at