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New research · Ophthalmology
NPJ digital medicine · 23h
Cross-sectionalNPJ digital medicine · 2026

Shifting the retinal foundation models paradigm from slices to volumes for optical coherence tomography.

Raphael Judkiewicz, Eran Berkowitz, Meishar Meisel … Joachim A Behar
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OphthalmologyCross-sectional

Video foundation model V-JEPA achieved an average AUROC of 0.94 for detecting retinal diseases.

Shifting the retinal foundation models paradigm from slices to volumes for optical coherence tomography.

Raphael Judkiewicz et al. · NPJ digital medicine · 2026
Background

Pretrained foundation models facilitate task-specific model development by enabling fine-tuning with limited labeled data.

Methods

Optical Coherence Tomography (OCT) is essential in ophthalmology for cross-sectional imaging of the retina.

0.94
Results
This represents high diagnostic accuracy for age-related macular degeneration and glaucomatous optic neuropathy.
More results

However, current foundation models rely on a single B-scan (usually the central slice), overlooking volumetric context.

This research investigates video foundation models to capture full 3D retinal structure and improve diagnostic performance.

More results

V-JEPA, a state-of-the-art video foundation model, was benchmarked against retinal foundation models (RETFound, VisionFM) and a natural image foundation model (DINOv2).

All were fine-tuned to detect Age-related Macular Degeneration or Glaucomatous Optic Neuropathy using five OCT datasets.

“
Conclusion

To our knowledge, this is the first application of transformer-based video models to volumetric OCT, highlighting their promise in 3D medical imaging.

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