Sophie Riedl

Orcid: 0009-0004-2911-3444

According to our database1, Sophie Riedl authored at least 15 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2019
2020
2021
2022
2023
2024
2025
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

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

An interactive task-based method for the avoidance of metal artifacts in CBCT.
Int. J. Comput. Assist. Radiol. Surg., July, 2024

Metadata-enhanced contrastive learning from retinal optical coherence tomography images.
Medical Image Anal., 2024

Specialist vision-language models for clinical ophthalmology.
CoRR, 2024

2023
Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT.
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

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


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