aceNoise-aware dynamic convolution for improved generalizability of retinal disease diagnosis using optical coherence tomography images
Significance Optical coherence tomography (OCT) is widely used for the diagnosis of retinal diseases. However, deep learning models trained on a single dataset often degrade when deployed across scanners and clinical sites due to device-dependent speckle variability and acquisition differences, limiting their reliability in real-world screening. Aim We aim to develop a lightweight deep learning framework that leverages speckle characteristics in OCT images to improve cross-scanner generalizability for retinal di…
Deep learning OCT models trained on a single dataset often degrade across scanners and sites due to device-dependent speckle variability, limiting reliability in real-world screening.
Evidence
- Peer-reviewedJournal of Biomedical Optics2026-08-12
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Truvace Impact Record TRV-2026-0775, v1: “Noise-aware dynamic convolution for improved generalizability of retinal disease diagnosis using optical coherence tomography images.” Truvace, 2026-08-15. /record/TRV-2026-0775 (accessed at citation time). sha256 d07c7c02319e5ea8…
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