Anomaly Detection in Retinal OCT Images With Deep Learning-Based Knowledge Distillation
Deep learning approaches can enable an automated and objective screening of a wide range of pathological retinal conditions that deviate from normal appearance.
Authors
- Ursula Schmidt‐Erfurth (ORCID: https://orcid.org/0000-0002-7788-7311)
- Guilherme Aresta (ORCID: https://orcid.org/0000-0002-4225-2156)
- Teresa Araújo (ORCID: https://orcid.org/0000-0001-9687-528X)
- Hrvoje Bogunović (ORCID: https://orcid.org/0000-0002-9168-0894)
Institutions
- Austrian Research Institute for Artificial Intelligence (AT)
- Medical University of Vienna (AT)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-03-27
- DOI
- https://doi.org/10.1167/tvst.14.3.26
- Citations
- 2
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.72