Automated Retinal Dysplasia Segmentation in Mouse Optical Coherence Tomography Scans Using a UNet-Based model
Apostolos V. Mikroulis, Miles Joseph Raishbrook, Marcela Pálková, Jiří Lindovský, Jan Procházka, Radislav Sedláček, Vendula Novosadová, Daniel Novak
The paper develops a UNet-based model for automated retinal dysplasia segmentation in mouse OCT scans, achieving high accuracy and consistency with expert annotations.
bioRxiv · Jun 6, 2026 · PreprintBioinformatics