Sophie Riedl
Orcid: 0000-0003-0003-0886Affiliations:
- Medical University of Vienna, Vienna, Austria
According to our database1,
Sophie Riedl
authored at least 25 papers
between 2016 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
npj Digit. Medicine, 2025
SD-LayerNet: Robust and label-efficient retinal layer segmentation via anatomical priors.
Comput. Methods Programs Biomed., 2025
2024
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression From Longitudinal OCTs.
IEEE Trans. Medical Imaging, September, 2024
Morph-SSL: Self-Supervision With Longitudinal Morphing for Forecasting AMD Progression From OCT Volumes.
IEEE Trans. Medical Imaging, September, 2024
Metadata-enhanced contrastive learning from retinal optical coherence tomography images.
Medical Image Anal., 2024
2023
CoRR, 2023
Morph-SSL: Self-Supervision with Longitudinal Morphing to Predict AMD Progression from OCT.
CoRR, 2023
Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration.
CoRR, 2023
Clustering Disease Trajectories in Contrastive Feature Space for Biomarker Proposal in Age-Related Macular Degeneration.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT: A PINNACLE Study Report.
Proceedings of the Ophthalmic Medical Image Analysis - 10th International Workshop, 2023
2022
SD-LayerNet: Semi-supervised Retinal Layer Segmentation in OCT Using Disentangled Representation with Anatomical Priors.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
TINC: Temporally Informed Non-contrastive Learning for Disease Progression Modeling in Retinal OCT Volumes.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2020
Correction to "Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT".
IEEE Trans. Medical Imaging, 2020
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT.
IEEE Trans. Medical Imaging, 2020
Correction to: On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems.
J. Math. Imaging Vis., 2020
On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems.
J. Math. Imaging Vis., 2020
2019
Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data.
IEEE Trans. Medical Imaging, 2019
IEEE Trans. Medical Imaging, 2019
On orthogonal projections for dimension reduction and applications in variational loss functions for learning problems.
CoRR, 2019
Modeling Disease Progression in Retinal OCTs with Longitudinal Self-supervised Learning.
Proceedings of the Predictive Intelligence in Medicine - Second International Workshop, 2019
An Amplified-Target Loss Approach for Photoreceptor Layer Segmentation in Pathological OCT Scans.
Proceedings of the Ophthalmic Medical Image Analysis - 6th International Workshop, 2019
U2-Net: A Bayesian U-Net Model With Epistemic Uncertainty Feedback For Photoreceptor Layer Segmentation In Pathological OCT Scans.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
2018
Fully Automated Segmentation of Hyperreflective Foci in Optical Coherence Tomography Images.
CoRR, 2018
2016