| Modeling disease progression in retinal OCTs with longitudinal self-supervised learning A Rivail, U Schmidt-Erfurth, WD Vogl, SM Waldstein, S Riedl, C Grechenig, ... Predictive Intelligence in Medicine: Second International Workshop, PRIME …, 2019 | 28 | 2019 |
| TINC: temporally informed non-contrastive learning for disease progression modeling in retinal OCT volumes T Emre, A Chakravarty, A Rivail, S Riedl, U Schmidt-Erfurth, H Bogunović International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 11 | 2022 |
| Deep survival modeling of longitudinal retinal OCT volumes for predicting the onset of atrophy in patients with intermediate AMD A Rivail, WD Vogl, S Riedl, C Grechenig, LM Coulibaly, GS Reiter, ... Biomedical Optics Express 14 (6), 2449-2464, 2023 | 7 | 2023 |
| Pretrained Deep 2.5 D Models for Efficient Predictive Modeling from Retinal OCT T Emre, M Oghbaie, A Chakravarty, A Rivail, S Riedl, J Mai, HPN Scholl, ... arXiv preprint arXiv:2307.13865, 2023 | 1 | 2023 |
| Identification of initial events leading to outer retinal atrophy in age-related macular degeneration using deep learning quantifications GS Reiter, S Riedl, A Rivail, J Mai, WD Vogl, C Grechenig, Z Wu, ... Investigative Ophthalmology & Visual Science 62 (8), 121-121, 2021 | 1 | 2021 |
| Topographic conversion model of outer retinal atrophy progression in intermediate age-related macular degeneration using deep learning A Rivail, GS Reiter, S Riedl, J Mai, WD Vogl, C Grechenig, Z Wu, ... Investigative Ophthalmology & Visual Science 62 (8), 130-130, 2021 | 1 | 2021 |
| Correction to: modeling disease progression in retinal OCTs with longitudinal self-supervised learning A Rivail, U Schmidt-Erfurth, WD Vogl, SM Waldstein, S Riedl, C Grechenig, ... Predictive Intelligence in Medicine: Second International Workshop, PRIME …, 2019 | 1 | 2019 |
| Predicting the individual risk of AMD progression from retinal OCT with intra-subject temporal consistency A Chakravarty, T Emre, D Lachinov, A Rivail, U Schmidt-Erfurth, ... Medical Imaging with Deep Learning, 2024 | | 2024 |
| 3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs T Emre, A Chakravarty, A Rivail, D Lachinov, O Leingang, S Riedl, J Mai, ... arXiv preprint arXiv:2312.16980, 2023 | | 2023 |
| Temporally Equivariant Contrastive Learning for Disease Progression T Emre, A Chakravarty, D Lachinov, A Rivail, U Schmidt-Erfurth, ... | | 2023 |
| Pretrained Deep 2.5 D Models for Efficient Predictive Modeling from Retinal OCT: A PINNACLE Study Report T Emre, M Oghbaie, A Chakravarty, A Rivail, S Riedl, J Mai, H PN Scholl, ... International Workshop on Ophthalmic Medical Image Analysis, 132-141, 2023 | | 2023 |
| Label-efficient retinal OCT classification and segmentation using image restoration-based self-supervised learning H Bogunovic, A Rivail, B Fazekas, D Lachinov, J Mai, U Schmidt-Erfurth Investigative Ophthalmology & Visual Science 64 (8), 5447-5447, 2023 | | 2023 |
| Deep Survival Prediction of Progression from Intermediate to Atrophic AMD from Longitudinal Retinal OCT A Rivail, WD Vogl, S Riedl, C Grechenig, GS Reiter, RH Guymer, Z Wu, ... Investigative Ophthalmology & Visual Science 63 (7), 3858-3858, 2022 | | 2022 |
| Retinal OCT Analysis and Prediction with Deep Learning H Bogunović, WD Vogl, P Seeböck, A Rivail Optical Coherence Tomography, OW2E. 1, 2020 | | 2020 |
| Prediction of disease conversion in intermediate AMD from longitudinal OCT using self-supervised deep learning A Rivail, WD Vogl, FG Schlanitz, M Baratsits, U Schmidt-Erfurth, ... Investigative Ophthalmology & Visual Science 60 (9), 1355-1355, 2019 | | 2019 |
| Unsupervised Representation Learning of Dynamic Retinal Image Changes by Predicting the Follow-up Image A Rivail, H Bogunović, BS Gerendas, SM Waldstein, WD Vogl, ... | | 2018 |
Hrvoje BogunovićMedical University of Vienna, AustriaBestätigte E-Mail-Adresse bei meduniwien.ac.at
