| 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 |
| 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 |
| Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT P Seeböck, JI Orlando, T Schlegl, SM Waldstein, H Bogunovic, ... IEEE Transactions on Medical Imaging 39 (1), 87 - 98, 2019 | 164 | 2019 |
| Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data P Seeböck, S Waldstein, S Klimscha, H Bogunovic, T Schlegl, ... IEEE Transactions on Medical Imaging 38 (4), 1037-1047, 2018 | 105 | 2018 |
| U2-net: A bayesian u-net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological oct scans JI Orlando, P Seeböck, H Bogunović, S Klimscha, C Grechenig, ... 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 79 | 2019 |
| METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII B Kocak, T Akinci D’Antonoli, N Mercaldo, A Alberich-Bayarri, B Baessler, ... Insights into imaging 15 (1), 8, 2024 | 69 | 2024 |
| AI-based monitoring of retinal fluid in disease activity and under therapy U Schmidt-Erfurth, GS Reiter, S Riedl, P Seeböck, WD Vogl, BA Blodi, ... Progress in retinal and eye research 86, 100972, 2022 | 65 | 2022 |
| Identifying and categorizing anomalies in retinal imaging data P Seeböck, S Waldstein, S Klimscha, BS Gerendas, R Donner, T Schlegl, ... arXiv preprint arXiv:1612.00686, 2016 | 61 | 2016 |
| Reducing image variability across OCT devices with unsupervised unpaired learning for improved segmentation of retina D Romo-Bucheli, P Seeböck, JI Orlando, BS Gerendas, SM Waldstein, ... Biomedical optics express 11 (1), 346-363, 2019 | 49 | 2019 |
| Automated quantification of macular fluid in retinal diseases and their response to anti-VEGF therapy M Michl, M Fabianska, P Seeböck, A Sadeghipour, BH Najeeb, ... British Journal of Ophthalmology 106 (1), 113-120, 2022 | 35 | 2022 |
| Using cyclegans for effectively reducing image variability across oct devices and improving retinal fluid segmentation P Seeböck, D Romo-Bucheli, S Waldstein, H Bogunovic, JI Orlando, ... 2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019 …, 2019 | 32 | 2019 |
| Fully automated segmentation of hyperreflective foci in optical coherence tomography images T Schlegl, H Bogunovic, S Klimscha, P Seeböck, A Sadeghipour, ... arXiv preprint arXiv:1805.03278, 2018 | 31 | 2018 |
| Projective skip-connections for segmentation along a subset of dimensions in retinal OCT D Lachinov, P Seeböck, J Mai, F Goldbach, U Schmidt-Erfurth, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 28 | 2021 |
| Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning SM Waldstein, P Seeböck, R Donner, A Sadeghipour, H Bogunović, ... Scientific reports 10 (1), 12954, 2020 | 27 | 2020 |
| Deep Learning In Medical Image Analysis P Seeböck Technical University of Vienna, 2015 | 18 | 2015 |
| Linking function and structure with ReSensNet: predicting retinal sensitivity from OCT using deep learning P Seeböck, WD Vogl, SM Waldstein, JI Orlando, M Baratsits, T Alten, ... Ophthalmology Retina 6 (6), 501-511, 2022 | 14 | 2022 |
| Unsupervised anomaly detection with generative adversarial networks to guide marker discovery (2017) T Schlegl, P Seeböck, SM Waldstein, U Schmidt-Erfurth, G Langs arXiv preprint arXiv:1703.05921, 0 | 13 | |
| Segmentation of macular neovascularization and leakage in fluorescein angiography images in neovascular age-related macular degeneration using deep learning D Holomcik, P Seeböck, BS Gerendas, G Mylonas, BH Najeeb, ... Eye 37 (7), 1439-1444, 2023 | 12 | 2023 |
| Assessment of RadiomIcS rEsearch (ARISE): a brief guide for authors, reviewers, and readers from the Scientific Editorial Board of European Radiology B Kocak, LL Chepelev, LC Chu, R Cuocolo, BS Kelly, P Seeböck, ... European radiology 33 (11), 7556-7560, 2023 | 11 | 2023 |
| Quality assessment of colour fundus and fluorescein angiography images using deep learning M König, P Seeböck, BS Gerendas, G Mylonas, R Winklhofer, ... British Journal of Ophthalmology 108 (1), 98-104, 2024 | 10 | 2024 |
Sebastian M. WaldsteinOphthalmology, Landesklinikum Mistelbach-GänserndorfVerified email at meduniwien.ac.at