Optimizing multi-dimensional retinal segmentation: a performance-practicality analysis
This study introduces a multi-dimensional framework to systematically evaluate the generalization and computational efficiency of deep learning models for retinal vessel segmentation. Using the DRIVE and STARE datasets, this research evaluates the performance of SegNet, U-Net, and DeepLab across in-domain, cross-domain...