The GEYEDANCE project is pleased to highlight a newly published study on IEEE Xplore titled: “Robust Distance Estimation with Out-of-distribution Detection in Ophthalmic Surgery” released in February, 2026.
This new IEEE‑published work introduces a deep learning method that improves micrometer‑scale instrument‑to‑retina distance estimation, a key factor for patient safety in ophthalmic surgery.
Validation on ex vivo human eyes shows strong performance: The pipeline achieves 88.8% accuracy in identifying out-of-distribution (OOD) measurements. Additionally, distance estimation improved by 89% and 93% when compared to two existing methods, resulting in an mean absolute error (MAE) of less than 40 μm across diverse conditions, including scans with blood and obstructions.
These results mark a major step forward in improving the accuracy of instrument-to-retina distance estimation thus enhancing patient safety in ophthalmic procedures. The approach opens new opportunities for sensor‑equipped instruments across various surgical disciplines, supporting the development of safer surgical systems.
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